Research

The research interests of the employees of the Department of Computational Intelligence include the broadly understood methods of computational intelligence and their application.

Papers (795)

Last Sync Date: 2024-05-12

2024 (17)

Circuit Implementation and Quasi-Stabilization of Delayed Inertial Memristor-Based Neural Networks
Xin Y., Cheng Z., Cao J., Rutkowski L., Wang Y., Circuit Implementation and Quasi-Stabilization of Delayed Inertial Memristor-Based Neural Networks, IEEE Transactions on Neural Networks and Learning Systems, 35, 35, 1394-1400, 2024, Cites: 6
Secure Data Deduplication With Dynamic Access Control for Mobile Cloud Storage
Qi S., Wei W., Wang J., Sun S., Rutkowski L., Huang T., Kacprzyk J., Qi Y., Secure Data Deduplication With Dynamic Access Control for Mobile Cloud Storage, IEEE Transactions on Mobile Computing, 23, 23, 2566-2582, 2024, Cites: 3
Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks
Huang Z., Lv W., Liu C., Xu Y., Rutkowski L., Huang T., Event-Triggered Distributed Moving Horizon Estimation Over Wireless Sensor Networks, IEEE Transactions on Industrial Informatics, 20, 20, 4218-4226, 2024, Cites: 1
A Second-Order Primal-Dual Dynamics for Set Constrained Distributed Optimization Problems
Tao M., Guo L., Cao J., Rutkowski L., A Second-Order Primal-Dual Dynamics for Set Constrained Distributed Optimization Problems, IEEE Transactions on Circuits and Systems II: Express Briefs, 71, 71, 1316-1320, 2024, Cites: 1
Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy
Lin L., Cao J., Lu J., Rutkowski L., Set Stabilization of Large-Scale Stochastic Boolean Networks: A Distributed Control Strategy, IEEE/CAA Journal of Automatica Sinica, 11, 11, 806-808, 2024, Cites: 1
A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains
Lin L., Cao J., Lam J., Rutkowski L., Dimirovski G.M., Zhu S., A Bisimulation-Based Foundation for Scale Reductions of Continuous-Time Markov Chains, IEEE Transactions on Automatic Control, 2024, Cites: 1
Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems with Switching Topologies
Lv X., Cao J., Rutkowski L., Duan P., Distributed Saturated Impulsive Control for Local Consensus of Nonlinear Time-Delay Multiagent Systems with Switching Topologies, IEEE Transactions on Automatic Control, 69, 69, 771-782, 2024, Cites: 1
Leader-Follower Consensus Over Finite Fields
Lin L., Cao J., Lam J., Zhu S., Azuma S., Rutkowski L., Leader-Follower Consensus Over Finite Fields, IEEE Transactions on Automatic Control, 2024, Cites: 1
Finite-Time Control of Fuzzy Competitive Networks via Comparison Method and Bounded Control
Kong F., Cao J., Rutkowski L., Zhang Y., Finite-Time Control of Fuzzy Competitive Networks via Comparison Method and Bounded Control, IEEE Transactions on Fuzzy Systems, 2024, Cites: 0
Accelerating deep neural network learning using data stream methodology
Duda P., Wojtulewicz M., Rutkowski L., Accelerating deep neural network learning using data stream methodology, Information Sciences, 669, 669, 2024, Cites: 0
Complex pattern evolution of a two-dimensional space diffusion model of malware spread
Cheng H., Xiao M., Lu Y., Bao H., Rutkowski L., Cao J., Complex pattern evolution of a two-dimensional space diffusion model of malware spread, Physica Scripta, 99, 99, 2024, Cites: 0
(μ +λ) Evolution Strategy with Socio-Cognitive Mutation
Urbanczyk A., Kucaba K., Wojtulewicz M., Kisiel-Dorohinicki M., Rutkowski L., Duda P., Kacprzyk J., Yao X., Chong S.Y., Byrski A., (μ +λ) Evolution Strategy with Socio-Cognitive Mutation, Journal of Automation, Mobile Robotics and Intelligent Systems, 18, 18, 1-11, 2024, Cites: 0
A multi-model approach to the development of algorithmic trading systems for the Forex market
Sevastjanov P., Kaczmarek K., Rutkowski L., A multi-model approach to the development of algorithmic trading systems for the Forex market, Expert Systems with Applications, 236, 236, 2024, Cites: 0
How to regulate pattern formations for malware propagation in cyber-physical systems
Cheng H., Xiao M., Yu W., Rutkowski L., Cao J., How to regulate pattern formations for malware propagation in cyber-physical systems, Chaos, 34, 34, 2024, Cites: 0
An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm
Slowik A., Cpalka K., Xue Y., Hapka A., An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm, Applied Energy, 364, 364, 2024, Cites: 0
Hybrid control of Turing instability and bifurcation for spatial-temporal propagation of computer virus
Ju Y., Xiao M., Huang C., Rutkowski L., Cao J., Hybrid control of Turing instability and bifurcation for spatial-temporal propagation of computer virus, International Journal of Systems Science, 2024, Cites: 0
Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel
Zhou Y., Lv W., Tao J., Xu Y., Huang T., Rutkowski L., Event-triggered impulsive quasi-synchronization for BAM neural networks with reliable redundant channel, Neural Networks, 169, 169, 485-495, 2024, Cites: 0

2023 (72)

Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol
Lin A., Cheng J., Rutkowski L., Wen S., Luo M., Cao J., Asynchronous Fault Detection for Memristive Neural Networks With Dwell-Time-Based Communication Protocol, IEEE Transactions on Neural Networks and Learning Systems, 34, 34, 9004-9015, 2023, Cites: 16
Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks
Bilski J., Smolag J., Kowalczyk B., Grzanek K., Izonin I., Fast Computational Approach to the Levenberg-Marquardt Algorithm for Training Feedforward Neural Networks, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 45-61, 2023, Cites: 12
Fuzzy H<inf>∞</inf> Control of Discrete-Time Nonlinear Markov Jump Systems via a Novel Hybrid Reinforcement Q-Learning Method
Wang J., Wu J., Shen H., Cao J., Rutkowski L., Fuzzy H<inf>∞</inf> Control of Discrete-Time Nonlinear Markov Jump Systems via a Novel Hybrid Reinforcement Q-Learning Method, IEEE Transactions on Cybernetics, 53, 53, 7380-7391, 2023, Cites: 11
A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism
Wang J., Wu J., Shen H., Cao J., Rutkowski L., A Decentralized Learning Control Scheme for Constrained Nonlinear Interconnected Systems Based on Dynamic Event-Triggered Mechanism, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53, 53, 4934-4943, 2023, Cites: 8
Observability and Detectability of Stochastic Labeled Graphs
Zhu S., Cao J., Lin L., Rutkowski L., Lu J., Lu G., Observability and Detectability of Stochastic Labeled Graphs, IEEE Transactions on Automatic Control, 68, 68, 7299-7311, 2023, Cites: 7
Observer-Based Control for Discrete-Time Hidden Semi-Markov Jump Systems
Shen H., Zhang Y., Wang J., Cao J., Rutkowski L., Observer-Based Control for Discrete-Time Hidden Semi-Markov Jump Systems, IEEE Transactions on Automatic Control, 68, 68, 6255-6261, 2023, Cites: 7
Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study
Nguyen H.-C., Nguyen T.-H., Scherer R., Le V.-H., Deep Learning for Human Activity Recognition on 3D Human Skeleton: Survey and Comparative Study, Sensors, 23, 23, 2023, Cites: 7
Stabilization of Markovian Jump Boolean Control Networks via Event-Triggered Control
Chen B., Cao J., Lu G., Rutkowski L., Stabilization of Markovian Jump Boolean Control Networks via Event-Triggered Control, IEEE Transactions on Automatic Control, 68, 68, 1215-1222, 2023, Cites: 6
YOLO Series for Human Hand Action Detection and Classification from Egocentric Videos
Nguyen H.-C., Nguyen T.-H., Scherer R., Le V.-H., YOLO Series for Human Hand Action Detection and Classification from Egocentric Videos, Sensors (Basel, Switzerland), 23, 23, 2023, Cites: 5
LSTM-SN: complex text classifying with LSTM fusion social network
Wei W., Li X., Zhang B., Li L., Damasevicius R., Scherer R., LSTM-SN: complex text classifying with LSTM fusion social network, Journal of Supercomputing, 79, 79, 9558-9583, 2023, Cites: 5
A New Approach to Image-Based Recommender Systems with the Application of Heatmaps Maps
Woldan P., Duda P., Cader A., Laktionov I., A New Approach to Image-Based Recommender Systems with the Application of Heatmaps Maps, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 63-72, 2023, Cites: 4
The L<inf>2</inf> convergence of stream data mining algorithms based on probabilistic neural networks
Rutkowska D., Duda P., Cao J., Rutkowski L., Byrski A., Jaworski M., Tao D., The L<inf>2</inf> convergence of stream data mining algorithms based on probabilistic neural networks, Information Sciences, 631, 631, 346-368, 2023, Cites: 3
Fuzzy H<inf>∞</inf> Control of Semi-Markov Jump Singularly Perturbed Nonlinear Systems With Partial Information and Actuator Saturation
Wang J., Chen Z., Shen H., Cao J., Rutkowski L., Fuzzy H<inf>∞</inf> Control of Semi-Markov Jump Singularly Perturbed Nonlinear Systems With Partial Information and Actuator Saturation, IEEE Transactions on Fuzzy Systems, 31, 31, 4374-4384, 2023, Cites: 3
Improving the Efficiency of the EMS-Based Smart City: A Novel Distributed Framework for Spatial Data
Chen G., Zou W., Jing W., Wei W., Scherer R., Improving the Efficiency of the EMS-Based Smart City: A Novel Distributed Framework for Spatial Data, IEEE Transactions on Industrial Informatics, 19, 19, 594-604, 2023, Cites: 3
A New Approach to Statistical Iterative Reconstruction Algorithm for a CT Scanner with Flying Focal Spot Using a Rebinning Method
Pluta P., A New Approach to Statistical Iterative Reconstruction Algorithm for a CT Scanner with Flying Focal Spot Using a Rebinning Method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 286-299, 2023, Cites: 2
A novel approach to intelligent monitoring of gas composition and light mode of greenhouse crop growing zone on the basis of fuzzy modelling and human-in-the-loop techniques
Laktionov I., Rutkowski L., Vovna O., Byrski A., Kabanets M., A novel approach to intelligent monitoring of gas composition and light mode of greenhouse crop growing zone on the basis of fuzzy modelling and human-in-the-loop techniques, Engineering Applications of Artificial Intelligence, 126, 126, 2023, Cites: 2
Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track
Wang Y., Yan J., Huang W., Rutkowski L., Cao J., Variable-order fractional derivative rutting depth prediction of asphalt pavement based on the RIOHTrack full-scale track, Science China Information Sciences, 66, 66, 2023, Cites: 2
Toward domain adaptation with open-set target data: Review of theory and computer vision applications
Ghaffari R., Helfroush M.S., Khosravi A., Kazemi K., Danyali H., Rutkowski L., Toward domain adaptation with open-set target data: Review of theory and computer vision applications, Information Fusion, 100, 100, 2023, Cites: 2
A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis
Izonin I., Tkachenko R., Gurbych O., Kovac M., Rutkowski L., Holoven R., A non-linear SVR-based cascade model for improving prediction accuracy of biomedical data analysis, Mathematical Biosciences and Engineering, 20, 20, 13398-13414, 2023, Cites: 2
AN INTELLIGENT APPROACH TO SHORT-TERM WIND POWER PREDICTION USING DEEP NEURAL NETWORKS
Niksa-Rynkiewicz T., Stomma P., Witkowska A., Rutkowska D., Slowik A., Cpalka K., Jaworek-Korjakowska J., Kolendo P., AN INTELLIGENT APPROACH TO SHORT-TERM WIND POWER PREDICTION USING DEEP NEURAL NETWORKS, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 197-210, 2023, Cites: 2
Dynamic Signature Verification Using Selected Regions
Zalasinski M., Duda P., Lota S., Cpalka K., Dynamic Signature Verification Using Selected Regions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 388-397, 2023, Cites: 1
IMAGINE Dataset: Digital Camera Identification Image BenchmarkinDataset
Bernacki J., Scherer R., IMAGINE Dataset: Digital Camera Identification Image BenchmarkinDataset, Proceedings of the International Conference on Security and Cryptography, 1, 1, 799-804, 2023, Cites: 1
Collaborative neurodynamic optimization for solving nonlinear equations
Guan H., Liu Y., Kou K.I., Cao J., Rutkowski L., Collaborative neurodynamic optimization for solving nonlinear equations, Neural Networks, 165, 165, 483-490, 2023, Cites: 1
Multi-population-based Algorithms with Different Migration Topologies and Their Improvement by Population Re-initialization
Lapa K., Multi-population-based Algorithms with Different Migration Topologies and Their Improvement by Population Re-initialization, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 399-414, 2023, Cites: 1
Autoencoder Neural Network for Detecting Non-human Web Traffic
Gabryel M., Lada D., Kocic M., Autoencoder Neural Network for Detecting Non-human Web Traffic, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 232-242, 2023, Cites: 1
FPGA-Based Optimization of Industrial Numerical Machine Tool Servo Drives
Przybyl A., FPGA-Based Optimization of Industrial Numerical Machine Tool Servo Drives, Electronics (Switzerland), 12, 12, 2023, Cites: 1
Special issue on deep interpretation of deep learning: prediction, representation, modeling and utilization
Zhang N., Wang J., Rutkowski L., Special issue on deep interpretation of deep learning: prediction, representation, modeling and utilization, Neural Computing and Applications, 35, 35, 9947-9949, 2023, Cites: 1
The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach
Duda P., Wojtulewicz M., Rutkowski L., The Analysis of Optimizers in Training Artificial Neural Networks Using the Streaming Approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 46-55, 2023, Cites: 0
Fast Estimation of Multidimensional Regression Functions by the Parzen Kernel-Based Method
Galkowski T., Krzyzak A., Fast Estimation of Multidimensional Regression Functions by the Parzen Kernel-Based Method, Communications in Computer and Information Science, 1791 CCIS, 1791 CCIS, 251-262, 2023, Cites: 0
Evolutionary Algorithms and Their Applications in Intelligent Systems
Slowik A., Cpalka K., Hassanien A.E., Evolutionary Algorithms and Their Applications in Intelligent Systems, Lecture Notes on Data Engineering and Communications Technologies, 184, 184, 143-153, 2023, Cites: 0
A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism
Dziwinski P., Bartczuk L., A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm with Self-Adaptation Mechanism, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 363-374, 2023, Cites: 0
On Speeding up the Levenberg-Marquardt Learning Algorithm
Bilski J., Kowalczyk B., Smolag J., On Speeding up the Levenberg-Marquardt Learning Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 12-22, 2023, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, v-vi, 2023, Cites: 0
A Novel ConvMixer Transformer Based Architecture for Violent Behavior Detection
Alfarano A., De Magistris G., Mongelli L., Russo S., Starczewski J., Napoli C., A Novel ConvMixer Transformer Based Architecture for Violent Behavior Detection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, 3-16, 2023, Cites: 0
Ultrasmall fully-convolution GVA-net for point cloud processing[Formula presented]
Walczak J., Najgebauer P., Wojciechowski A., Scherer R., Ultrasmall fully-convolution GVA-net for point cloud processing[Formula presented], Applied Soft Computing, 132, 132, 2023, Cites: 0
A New Rebinning Reconstruction Method for the Low Dose CT Scanners with Flying Focal Spot
Pluta P., Cierniak R., A New Rebinning Reconstruction Method for the Low Dose CT Scanners with Flying Focal Spot, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, 269-278, 2023, Cites: 0
Edge Detection-Based Full-Disc Solar Image Hashing
Grycuk R., Najgebauer P., Scherer R., Edge Detection-Based Full-Disc Solar Image Hashing, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 243-251, 2023, Cites: 0
Visual Odometry with Depth-Wise Separable Convolution and Quaternion Neural Networks
De Magistris G., Comminiello D., Napoli C., Starczewski J.T., Visual Odometry with Depth-Wise Separable Convolution and Quaternion Neural Networks, CEUR Workshop Proceedings, 3417, 3417, 70-80, 2023, Cites: 0
A New Linguistic Fuzzy PRISM Algorithm
Bartczuk L., A New Linguistic Fuzzy PRISM Algorithm, IEEE International Conference on Fuzzy Systems, 2023, Cites: 0
Transformer-Based Original Content Recovery from Obfuscated PowerShell Scripts
Dedek M., Scherer R., Transformer-Based Original Content Recovery from Obfuscated PowerShell Scripts, Communications in Computer and Information Science, 1794 CCIS, 1794 CCIS, 284-295, 2023, Cites: 0
Distributed online bandit tracking for Nash equilibrium under partial-decision information setting
Feng Z.C., Xu W.Y., Cao J.D., Yang S.F., Rutkowski L., Distributed online bandit tracking for Nash equilibrium under partial-decision information setting, Science China Technological Sciences, 66, 66, 3129-3138, 2023, Cites: 0
InDecGAN: Learning to Generate Complex Images from Captions via Independent Object-Level Decomposition and Enhancement
Cheng J., Wu F., Liu L., Zhang Q., Rutkowski L., Tao D., InDecGAN: Learning to Generate Complex Images from Captions via Independent Object-Level Decomposition and Enhancement, IEEE Transactions on Multimedia, 25, 25, 8279-8293, 2023, Cites: 0
A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization
Sevastjanov P., Kaczmarek K., Rutkowski L., A currency trading system based on simplified models using fuzzy multi-criteria hierarchical optimization, Applied Soft Computing, 147, 147, 2023, Cites: 0
Detecting Sensitive Data with GANs and Fully Convolutional Networks
Korytkowski M., Nowak J., Scherer R., Detecting Sensitive Data with GANs and Fully Convolutional Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13995 LNAI, 13995 LNAI, 273-283, 2023, Cites: 0
Convergence of RBF Networks Regression Function Estimates and Classifiers
Krzyzak A., Galkowski T., Partyka M., Convergence of RBF Networks Regression Function Estimates and Classifiers, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13588 LNAI, 13588 LNAI, 363-376, 2023, Cites: 0
On Computing Paradigms - Where Will Large Language Models Be Going
Wu X., Zhu X., Baralis E., Lu R., Kumar V., Rutkowski L., Tang J., On Computing Paradigms - Where Will Large Language Models Be Going, Proceedings - IEEE International Conference on Data Mining, ICDM, 1577-1582, 2023, Cites: 0
Two-Dimensional Pheromone in Ant Colony Optimization
Starzec G., Starzec M., Bandyopadhyay S., Maulik U., Rutkowski L., Kisiel-Dorohinicki M., Byrski A., Two-Dimensional Pheromone in Ant Colony Optimization, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14162 LNAI, 14162 LNAI, 459-471, 2023, Cites: 0
A Novel Approach to the GQR Algorithm for Neural Networks Training
Bilski J., Kowalczyk B., A Novel Approach to the GQR Algorithm for Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 3-11, 2023, Cites: 0
Previous Opinions is All You Need—Legal Information Retrieval System
Osowski M., Lorenc K., Drozda P., Scherer R., Szalapak K., Komar-Komarowski K., Szymanski J., Sobecki A., Previous Opinions is All You Need—Legal Information Retrieval System, Communications in Computer and Information Science, 1864 CCIS, 1864 CCIS, 57-67, 2023, Cites: 0
A NEW APPROACH TO DETECTING AND PREVENTING POPULATIONS STAGNATION THROUGH DYNAMIC CHANGES IN MULTI-POPULATION-BASED ALGORITHMS
Lapa K., Rutkowska D., Byrski A., Napoli C., A NEW APPROACH TO DETECTING AND PREVENTING POPULATIONS STAGNATION THROUGH DYNAMIC CHANGES IN MULTI-POPULATION-BASED ALGORITHMS, Journal of Artificial Intelligence and Soft Computing Research, 13, 13, 289-306, 2023, Cites: 0
Cryptographic Algorithms with Data Shorter than the Encryption Key, Based on LZW and Huffman Coding
Krokosz T., Rykowski J., Zajecka M., Brzoza-Woch R., Rutkowski L., Cryptographic Algorithms with Data Shorter than the Encryption Key, Based on LZW and Huffman Coding, Sensors, 23, 23, 2023, Cites: 0
Fuzzy-Based Solar Magnetogram Image Retrieval
Grycuk R., Korytkowski M., Scherer R., Fuzzy-Based Solar Magnetogram Image Retrieval, IEEE International Conference on Fuzzy Systems, 2023, Cites: 0
A New Statistical Approach to Image Reconstruction with Rebinning for the X-Ray CT Scanners with Flying Focal Spot Tube
Pluta P., Cierniak R., A New Statistical Approach to Image Reconstruction with Rebinning for the X-Ray CT Scanners with Flying Focal Spot Tube, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14074 LNCS, 14074 LNCS, 670-677, 2023, Cites: 0
Hand Gesture Recognition for Medical Purposes Using CNN
Sosnowski J., Pluta P., Najgebauer P., Hand Gesture Recognition for Medical Purposes Using CNN, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 80-88, 2023, Cites: 0
Multi-population Algorithm Using Surrogate Models and Different Training Plans
Kucharski D., Cpalka K., Multi-population Algorithm Using Surrogate Models and Different Training Plans, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 385-398, 2023, Cites: 0
Forecasting of solar energy production using the NEXO platform and VRM Portal
Dudzik S., Kowalczyk B., Forecasting of solar energy production using the NEXO platform and VRM Portal, Przeglad Elektrotechniczny, 2023, 2023, 224-227, 2023, Cites: 0
Socio-cognitive caste-based optimization
Urbanczyk A., Kipinski P., Nabywaniec M., Rutkowski L., Chong S.Y., Yao X., Boryczko K., Byrski A., Socio-cognitive caste-based optimization, Journal of Computational Science, 72, 72, 2023, Cites: 0
Profiling of Webshop Users in Terms of Price Sensitivity
Kocic E., Gabryel M., Kocic M., Profiling of Webshop Users in Terms of Price Sensitivity, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14125 LNAI, 14125 LNAI, 522-529, 2023, Cites: 0
Discovery of New Words in Tax-related Fields Based on Word Vector Representation
Wei W., Liu W., Zhang B., Scherer R., Damasevicius R., Discovery of New Words in Tax-related Fields Based on Word Vector Representation, Journal of Internet Technology, 24, 24, 923-930, 2023, Cites: 0
Guest Editorial Introduction to the Special Issue on Graph-Based Machine Learning for Intelligent Transportation Systems
Wei W., Chen K.-C., Rayes A., Scherer R., Guest Editorial Introduction to the Special Issue on Graph-Based Machine Learning for Intelligent Transportation Systems, IEEE Transactions on Intelligent Transportation Systems, 24, 24, 8393-8398, 2023, Cites: 0
Leader-following consensus of finite-field networks with time-delays
Zhu W., Cao J., Shi X., Rutkowski L., Leader-following consensus of finite-field networks with time-delays, Information Sciences, 647, 647, 2023, Cites: 0
A New Method of Verification of Dynamic Signatures Changing over Time with Decomposition and Selection of Characteristic Descriptors
Mastalerczyk M., Szczepanik T., Zalasinski M., A New Method of Verification of Dynamic Signatures Changing over Time with Decomposition and Selection of Characteristic Descriptors, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, 251-257, 2023, Cites: 0
Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks
Korytkowski M., Nowak J., Scherer R., Wei W., Privacy Preserving by Removing Sensitive Data from Documents with Fully Convolutional Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 277-285, 2023, Cites: 0
A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks
Lucas T.J., De Figueiredo I.S., Tojeiro C.A.C., De Almeida A.M.G., Scherer R., Brega J.R.F., Papa J.P., Da Costa K.A.P., A Comprehensive Survey on Ensemble Learning-Based Intrusion Detection Approaches in Computer Networks, IEEE Access, 11, 11, 122638-122676, 2023, Cites: 0
Editorial: Big data and artificial intelligence technologies for smart forestry
Jing W., Kuang Z., Scherer R., Wozniak M., Editorial: Big data and artificial intelligence technologies for smart forestry, Frontiers in Plant Science, 14, 14, 2023, Cites: 0
Fast Visual Imperfection Detection when Real Negative Examples are Unavailable
Najgebauer P., Scherer R., Grycuk R., Walczak J., Wojciechowski A., Lada-Tondyra E., Fast Visual Imperfection Detection when Real Negative Examples are Unavailable, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, 58-68, 2023, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, v-vi, 2023, Cites: 0
A New Computational Approach to the Levenberg-Marquardt Learning Algorithm
Bilski J., Kowalczyk B., Smolag J., A New Computational Approach to the Levenberg-Marquardt Learning Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13588 LNAI, 13588 LNAI, 16-26, 2023, Cites: 0
Employee Turnover Prediction From Email Communication Analysis
Korytkowski M., Nowak J., Scherer R., Zbieg A., Zak B., Relikowska G., Mader P., Employee Turnover Prediction From Email Communication Analysis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13589 LNAI, 13589 LNAI, 252-263, 2023, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14126 LNAI, 14126 LNAI, v-vi, 2023, Cites: 0
Remarks on Speeding up the Digital Camera Identification using Convolutional Neural Networks
Bernacki J., Scherer R., Remarks on Speeding up the Digital Camera Identification using Convolutional Neural Networks, Vietnam Journal of Computer Science, 10, 10, 537-555, 2023, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13588 LNAI, 13588 LNAI, v-vi, 2023, Cites: 0

2022 (50)

Synchronization of Neural Networks via Periodic Self-Triggered Impulsive Control and Its Application in Image Encryption
Tan X., Xiang C., Cao J., Xu W., Wen G., Rutkowski L., Synchronization of Neural Networks via Periodic Self-Triggered Impulsive Control and Its Application in Image Encryption, IEEE Transactions on Cybernetics, 52, 52, 8246-8257, 2022, Cites: 42
Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control
Yu T., Cao J., Rutkowski L., Luo Y.-P., Finite-Time Synchronization of Complex-Valued Memristive-Based Neural Networks via Hybrid Control, IEEE Transactions on Neural Networks and Learning Systems, 33, 33, 3938-3947, 2022, Cites: 33
A Fixed-Time Distributed Optimization Algorithm Based on Event-Triggered Strategy
Song Y., Cao J., Rutkowski L., A Fixed-Time Distributed Optimization Algorithm Based on Event-Triggered Strategy, IEEE Transactions on Network Science and Engineering, 9, 9, 1154-1162, 2022, Cites: 33
An Explainable Fake News Detector Based on Named Entity Recognition and Stance Classification Applied to COVID-19
De Magistris G., Russo S., Roma P., Starczewski J.T., Napoli C., An Explainable Fake News Detector Based on Named Entity Recognition and Stance Classification Applied to COVID-19, Information (Switzerland), 13, 13, 2022, Cites: 27
Fuzzy clustering decomposition of genetic algorithm-based instance selection for regression problems
Kordos M., Blachnik M., Scherer R., Fuzzy clustering decomposition of genetic algorithm-based instance selection for regression problems, Information Sciences, 587, 587, 23-40, 2022, Cites: 19
Robust Composite H<inf>∞</inf>Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method
Shen H., Wang X., Wang J., Cao J., Rutkowski L., Robust Composite H<inf>∞</inf>Synchronization of Markov Jump Reaction-Diffusion Neural Networks via a Disturbance Observer-Based Method, IEEE Transactions on Cybernetics, 52, 52, 12712-12721, 2022, Cites: 18
Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays
Li H., Fang J.-A., Li X., Rutkowski L., Huang T., Event-Triggered Synchronization of Multiple Discrete-Time Markovian Jump Memristor- Based Neural Networks With Mixed Mode-Dependent Delays, IEEE Transactions on Circuits and Systems I: Regular Papers, 69, 69, 2095-2107, 2022, Cites: 17
Hybrid approaches to nature-inspired population-based intelligent optimization for industrial applications
Slowik A., Cpalka K., Hybrid approaches to nature-inspired population-based intelligent optimization for industrial applications, IEEE Transactions on Industrial Informatics, 18, 18, 546-558, 2022, Cites: 17
Event-Triggered Finite-Time Guaranteed Cost H-Infinity Consensus for Nonlinear Uncertain Multi-Agent Systems
Luo Y., Zhu W., Cao J., Rutkowski L., Event-Triggered Finite-Time Guaranteed Cost H-Infinity Consensus for Nonlinear Uncertain Multi-Agent Systems, IEEE Transactions on Network Science and Engineering, 9, 9, 1527-1539, 2022, Cites: 14
Unified End-to-End YOLOv5-HR-TCM Framework for Automatic 2D/3D Human Pose Estimation for Real-Time Applications
Nguyen H.-C., Nguyen T.-H., Scherer R., Le V.-H., Unified End-to-End YOLOv5-HR-TCM Framework for Automatic 2D/3D Human Pose Estimation for Real-Time Applications, Sensors, 22, 22, 2022, Cites: 14
Stabilization of Markovian Jump Boolean Control Networks via Sampled-Data Control
Chen B., Cao J., Lu G., Rutkowski L., Stabilization of Markovian Jump Boolean Control Networks via Sampled-Data Control, IEEE Transactions on Cybernetics, 52, 52, 10290-10301, 2022, Cites: 13
Event-Triggering Interaction Scheme for Discrete-Time Decentralized Optimization with Nonuniform Step Sizes
Feng Y., Zhang W., Xiong J., Li H., Rutkowski L., Event-Triggering Interaction Scheme for Discrete-Time Decentralized Optimization with Nonuniform Step Sizes, IEEE Transactions on Cybernetics, 52, 52, 748-757, 2022, Cites: 11
Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification
Hammad M., Meshoul S., Dziwinski P., Plawiak P., Elgendy I.A., Efficient Lightweight Multimodel Deep Fusion Based on ECG for Arrhythmia Classification, Sensors, 22, 22, 2022, Cites: 9
A New Approach to Descriptors Generation for Image Retrieval by Analyzing Activations of Deep Neural Network Layers
Staszewski P., Jaworski M., Cao J., Rutkowski L., A New Approach to Descriptors Generation for Image Retrieval by Analyzing Activations of Deep Neural Network Layers, IEEE Transactions on Neural Networks and Learning Systems, 33, 33, 7913-7920, 2022, Cites: 9
Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm
Bilski J., Kowalczyk B., Kisiel-Dorohinicki M., Siwocha A., Zurada J., Towards a Very Fast Feedforward Multilayer Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 181-195, 2022, Cites: 9
MSAR-DefogNet: Lightweight cloud removal network for high resolution remote sensing images based on multi scale convolution
Zhou Y., Jing W., Wang J., Chen G., Scherer R., Damasevicius R., MSAR-DefogNet: Lightweight cloud removal network for high resolution remote sensing images based on multi scale convolution, IET Image Processing, 16, 16, 659-668, 2022, Cites: 8
General Decay Stability for Nonautonomous Neutral Stochastic Systems with Time-Varying Delays and Markovian Switching
Feng L., Liu L., Cao J., Rutkowski L., Lu G., General Decay Stability for Nonautonomous Neutral Stochastic Systems with Time-Varying Delays and Markovian Switching, IEEE Transactions on Cybernetics, 52, 52, 5441-5453, 2022, Cites: 8
Detecting Anomalies in Advertising Web Traffic with the Use of the Variational Autoencoder
Gabryel M., Lada D., Filutowicz Z., Patora-Wysocka Z., Kisiel-Dorohinicki M., Chen G.Y., Detecting Anomalies in Advertising Web Traffic with the Use of the Variational Autoencoder, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 255-256, 2022, Cites: 8
Synchronization of Finite-Field Networks With Time Delays
Zhu W., Cao J., Shi X., Rutkowski L., Synchronization of Finite-Field Networks With Time Delays, IEEE Transactions on Network Science and Engineering, 9, 9, 347-355, 2022, Cites: 8
Overview of Capsule Neural Networks
Sun Z., Zhao G., Scherer R., Wei W., Wozniak M., Overview of Capsule Neural Networks, Journal of Internet Technology, 23, 23, 33-44, 2022, Cites: 8
Hierarchical interactive demand response power profile tracking optimization and control of multiple EV aggregators
Hu J., Cao J., Rutkowski L., Xue C., Yu J., Hierarchical interactive demand response power profile tracking optimization and control of multiple EV aggregators, Electric Power Systems Research, 208, 208, 2022, Cites: 8
Deep Learning Methods in Short-Term Traffic Prediction: A Survey
Hou Y., Zheng X., Han C., Wei W., Scherer R., Polap D., Deep Learning Methods in Short-Term Traffic Prediction: A Survey, Information Technology and Control, 51, 51, 139-157, 2022, Cites: 7
Guest Editorial: Hybrid Approaches to Nature-Inspired Population-Based Intelligent Optimization for Industrial Applications
Slowik A., Cpalka K., Guest Editorial: Hybrid Approaches to Nature-Inspired Population-Based Intelligent Optimization for Industrial Applications, IEEE Transactions on Industrial Informatics, 18, 18, 542-545, 2022, Cites: 7
Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach
Zalasinski M., Laskowski L., Niksa-Rynkiewicz T., Cpalka K., Byrski A., Przybyszewski K., Trippner P., Dong S., Evolutionary Algorithm for Selecting Dynamic Signatures Partitioning Approach, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 267-279, 2022, Cites: 5
Multi-Population-Based Algorithm with an Exchange of Training Plans Based on Population Evaluation
Lapa K., Cpalka K., Kisiel-Dorohinicki M., Paszkowski J., Debski M., Le V.-H., Multi-Population-Based Algorithm with an Exchange of Training Plans Based on Population Evaluation, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 239-253, 2022, Cites: 4
Semantic Hashing for Fast Solar Magnetogram Retrieval
Grycuk R., Scherer R., Marchlewska A., Napoli C., Semantic Hashing for Fast Solar Magnetogram Retrieval, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 299-306, 2022, Cites: 4
Noise Robust Illumination Invariant Face Recognition Via Bivariate Wavelet Shrinkage in Logarithm Domain
Chen G.Y., Krzyzak A., Duda P., Cader A., Noise Robust Illumination Invariant Face Recognition Via Bivariate Wavelet Shrinkage in Logarithm Domain, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 169-180, 2022, Cites: 4
A population-based algorithm with the selection of evaluation precision and size of the population
Cpalka K., Slowik A., Lapa K., A population-based algorithm with the selection of evaluation precision and size of the population, Applied Soft Computing, 115, 115, 2022, Cites: 3
Digital camera identification by fingerprint’s compact representation
Bernacki J., Digital camera identification by fingerprint’s compact representation, Multimedia Tools and Applications, 81, 81, 21641-21674, 2022, Cites: 2
Formation Control of Multi-Agent Systems With Constrained Mismatched Compasses
Li Z., Tang Y., Fan Y., Huang T., Rutkowski L., Formation Control of Multi-Agent Systems With Constrained Mismatched Compasses, IEEE Transactions on Network Science and Engineering, 9, 9, 2224-2236, 2022, Cites: 2
A Novel Approach to Type-Reduction and Design of Interval Type-2 Fuzzy Logic Systems
Starczewski J.T., Przybyszewski K., Byrski A., Szmidt E., Napoli C., A Novel Approach to Type-Reduction and Design of Interval Type-2 Fuzzy Logic Systems, Journal of Artificial Intelligence and Soft Computing Research, 12, 12, 197-206, 2022, Cites: 2
Fast Estimation of Multidimensional Regression Functions
Galkowski T., Krzyzak A., Dziwinski P., Fast Estimation of Multidimensional Regression Functions, 2022 17th International Conference on Control, Automation, Robotics and Vision, ICARCV 2022, 211-216, 2022, Cites: 1
Individual Source Camera Identification with Convolutional Neural Networks
Bernacki J., Costa K.A.P., Scherer R., Individual Source Camera Identification with Convolutional Neural Networks, Communications in Computer and Information Science, 1716 CCIS, 1716 CCIS, 45-55, 2022, Cites: 1
An Ensemble Pruning Approach to Optimize Intrusion Detection Systems Performance
Lucas T.J., Da Costa K.A.P., Scherer R., Papa J.P., An Ensemble Pruning Approach to Optimize Intrusion Detection Systems Performance, Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, 2022-October, 2022-October, 1173-1179, 2022, Cites: 1
A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder
Grycuk R., Galkowski T., Scherer R., Rutkowski L., A Novel Method for Solar Image Retrieval Based on the Parzen Kernel Estimate of the Function Derivative and Convolutional Autoencoder, Proceedings of the International Joint Conference on Neural Networks, 2022-July, 2022-July, 2022, Cites: 1
Applying autonomous hybrid agent-based computing to difficult optimization problems
Godzik M., Dajda J., Kisiel-Dorohinicki M., Byrski A., Rutkowski L., Orzechowski P., Wagenaar J., Moore J.H., Applying autonomous hybrid agent-based computing to difficult optimization problems, Journal of Computational Science, 64, 64, 2022, Cites: 1
Digital forensics: a fast algorithm for a digital sensor identification
Bernacki J., Scherer R., Digital forensics: a fast algorithm for a digital sensor identification, Journal of Information and Telecommunication, 6, 6, 399-419, 2022, Cites: 0
Special issue on deep learning for time series data
Ma R., Angryk R., Scherer R., Special issue on deep learning for time series data, Neural Computing and Applications, 34, 34, 13147-13148, 2022, Cites: 0
From Network Package Flow to Images: How to Accurately Detect Anomalies in Computer Networks
Junior P.R.G.H., Scherer R., Januario L.B., Rodrigues D., Papa J.P., Costa K.A.P., From Network Package Flow to Images: How to Accurately Detect Anomalies in Computer Networks, International Conference on Systems, Signals, and Image Processing, 2022-June, 2022-June, 2022, Cites: 0
Editorial: Special Issue on Reliable Machine Learning and Optimization
Zhang N., Wang J., Rutkowski L., Editorial: Special Issue on Reliable Machine Learning and Optimization, International Journal on Artificial Intelligence Tools, 31, 31, 2022, Cites: 0
Local Search in Selected Crossover Operators
Kordos M., Kulka R., Steblik T., Scherer R., Local Search in Selected Crossover Operators, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13352 LNCS, 13352 LNCS, 369-382, 2022, Cites: 0
Two Novel Methods for Multiple Kinect v2 Sensor Calibration
Hazra S., Pisipati M., Puhan A., Nandy A., Scherer R., Two Novel Methods for Multiple Kinect v2 Sensor Calibration, Communications in Computer and Information Science, 1568 CCIS, 1568 CCIS, 403-414, 2022, Cites: 0
Fast Solar Image Retrieval and Classification by Fuzzy Rules
Grycuk R., Korytkowski M., Scherer R., Drozda P., Wei W., Kordos M., Fast Solar Image Retrieval and Classification by Fuzzy Rules, IEEE International Conference on Fuzzy Systems, 2022-July, 2022-July, 2022, Cites: 0
An Original Continuous-to-Continuous Forward Model as a Universal Method for the Formulation of Reconstruction Methods for Medical Imaging Techniques
Cierniak R., Pluta P., An Original Continuous-to-Continuous Forward Model as a Universal Method for the Formulation of Reconstruction Methods for Medical Imaging Techniques, Communications in Computer and Information Science, 1653 CCIS, 1653 CCIS, 396-405, 2022, Cites: 0
A Real-time Hand Gesture Recognition System for Human-Computer and Human-Robot Interaction
Ponzi V., Iacobelli E., Napoli C., Starczewski J., A Real-time Hand Gesture Recognition System for Human-Computer and Human-Robot Interaction, CEUR Workshop Proceedings, 3398, 3398, 52-58, 2022, Cites: 0
A Novel DWT-based Encoder for Human Pose Estimation
De Magistris G., Romano M., Starczewski J., Napoli C., A Novel DWT-based Encoder for Human Pose Estimation, CEUR Workshop Proceedings, 3360, 3360, 33-40, 2022, Cites: 0
Continuous-to-Continuous Data Model vs. Discrete-to-Discrete Data Model for the Statistical Iterative Reconstruction Method
Cierniak R., Continuous-to-Continuous Data Model vs. Discrete-to-Discrete Data Model for the Statistical Iterative Reconstruction Method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13351 LNCS, 13351 LNCS, 493-506, 2022, Cites: 0
Real-time application of OPF-based classifier in Snort IDS
Utimura L., Costa K., Scherer R., Real-time application of OPF-based classifier in Snort IDS, Optimum-Path Forest: Theory, Algorithms, and Applications, 55-93, 2022, Cites: 0
Hypergraph-partitioning-based online joint scheduling of tasks and data
Song Y., Wang L., Xiao L., Wei W., Scherer R., Qin G., Wang J., Hypergraph-partitioning-based online joint scheduling of tasks and data, Journal of Supercomputing, 78, 78, 16088-16117, 2022, Cites: 0
Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot
Cierniak R., Bilski J., Pluta P., Implementations of statistical reconstruction algorithm for CT scanners with flying focal spot, Proceedings of SPIE - The International Society for Optical Engineering, 12304, 12304, 2022, Cites: 0

2021 (58)

Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters
Wang J., Yang C., Shen H., Cao J., Rutkowski L., Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 51, 7579-7586, 2021, Cites: 108
Synchronization of Switched Discrete-Time Neural Networks via Quantized Output Control with Actuator Fault
Yang X., Wan X., Zunshui C., Cao J., Liu Y., Rutkowski L., Synchronization of Switched Discrete-Time Neural Networks via Quantized Output Control with Actuator Fault, IEEE Transactions on Neural Networks and Learning Systems, 32, 32, 4191-4201, 2021, Cites: 83
Penalty method for constrained distributed quaternion-variable optimization
Xia Z., Liu Y., Lu J., Cao J., Rutkowski L., Penalty method for constrained distributed quaternion-variable optimization, IEEE Transactions on Cybernetics, 51, 51, 5631-5636, 2021, Cites: 41
Distributed Dynamic Self-Triggered Impulsive Control for Consensus Networks: The Case of Impulse Gain with Normal Distribution
Tan X., Cao J., Rutkowski L., Lu G., Distributed Dynamic Self-Triggered Impulsive Control for Consensus Networks: The Case of Impulse Gain with Normal Distribution, IEEE Transactions on Cybernetics, 51, 51, 624-634, 2021, Cites: 38
Short-Term Load Forecasting Based on Adabelief Optimized Temporal Convolutional Network and Gated Recurrent Unit Hybrid Neural Network
Shi H., Wang L., Scherer R., Wozniak M., Zhang P., Wei W., Short-Term Load Forecasting Based on Adabelief Optimized Temporal Convolutional Network and Gated Recurrent Unit Hybrid Neural Network, IEEE Access, 9, 9, 66965-66981, 2021, Cites: 37
Abnormal Detection of Electricity Consumption of User Based on Particle Swarm Optimization and Long Short Term Memory with the Attention Mechanism
Bian J., Wang L., Scherer R., Wozniak M., Zhang P., Wei W., Abnormal Detection of Electricity Consumption of User Based on Particle Swarm Optimization and Long Short Term Memory with the Attention Mechanism, IEEE Access, 9, 9, 47252-47265, 2021, Cites: 23
A novel method for speed training acceleration of recurrent neural networks
Bilski J., Rutkowski L., Smolag J., Tao D., A novel method for speed training acceleration of recurrent neural networks, Information Sciences, 553, 553, 266-279, 2021, Cites: 19
Review of road segmentation for sar images
Sun Z., Geng H., Lu Z., Scherer R., Wozniak M., Review of road segmentation for sar images, Remote Sensing, 13, 13, 1-15, 2021, Cites: 17
A Novel Fast Feedforward Neural Networks Training Algorithm
Bilski J., Kowalczyk B., Marjanski A., Gandor M., Zurada J., A Novel Fast Feedforward Neural Networks Training Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 287-306, 2021, Cites: 14
Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control
Lv X., Cao J., Rutkowski L., Dynamical and static multisynchronization analysis for coupled multistable memristive neural networks with hybrid control, Neural Networks, 143, 143, 515-524, 2021, Cites: 13
A Novel Grid-Based Clustering Algorithm
Starczewski A., Scherer M.M., Ksiek W., Debski M., Wang L., A Novel Grid-Based Clustering Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 319-330, 2021, Cites: 12
Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network
Niksa-Rynkiewicz T., Szewczuk-Krypa N., Witkowska A., Cpalka K., Zalasinski M., Cader A., Monitoring regenerative heat exchanger in steam power plant by making use of the recurrent neural network, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 143-155, 2021, Cites: 12
Sitsen: Passive sitting posture sensing based on wireless devices
Li M., Jiang Z., Liu Y., Chen S., Wozniak M., Scherer R., Damasevicius R., Wei W., Li Z., Li Z., Sitsen: Passive sitting posture sensing based on wireless devices, International Journal of Distributed Sensor Networks, 17, 17, 2021, Cites: 11
Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System with Heuristic Method
Xu S., Cao J., Liu Q., Rutkowski L., Optimal Control on Finite-Time Consensus of the Leader-Following Stochastic Multiagent System with Heuristic Method, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 51, 3617-3628, 2021, Cites: 11
Humannet-a two-tiered deep neural network architecture for self-occluding humanoid pose reconstruction
Kulikajevas A., Maskeliunas R., Damasevicius R., Scherer R., Humannet-a two-tiered deep neural network architecture for self-occluding humanoid pose reconstruction, Sensors, 21, 21, 2021, Cites: 11
Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm
Dziwinski P., Przybyl A., Trippner P., Paszkowski J., Hayashi Y., Hardware implementation of a Takagi-Sugeno neuro-fuzzy system optimized by a population algorithm, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 243-266, 2021, Cites: 10
Fixed-point arithmetic unit with a scaling mechanism for fpga-based embedded systems
Przybyl A., Fixed-point arithmetic unit with a scaling mechanism for fpga-based embedded systems, Electronics (Switzerland), 10, 10, 2021, Cites: 8
Decision Making Support System for Managing Advertisers by Ad Fraud Detection
Gabryel M., Scherer M.M., Sulkowski L., Damasevicius R., Decision Making Support System for Managing Advertisers by Ad Fraud Detection, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 331-339, 2021, Cites: 8
A New Statistical Reconstruction Method for the Computed Tomography Using an X-Ray Tube with Flying Focal Spot
Cierniak R., Pluta P., Waligora M., Szymanski Z., Grzanek K., Palka F., Piuri V., A New Statistical Reconstruction Method for the Computed Tomography Using an X-Ray Tube with Flying Focal Spot, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 271-286, 2021, Cites: 8
A Novel Method for Invariant Image Reconstruction
Pawlak M., Panesar G.S., Korytkowski M., A Novel Method for Invariant Image Reconstruction, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 69-80, 2021, Cites: 7
Robustness of digital camera identification with convolutional neural networks
Bernacki J., Robustness of digital camera identification with convolutional neural networks, Multimedia Tools and Applications, 80, 80, 29657-29673, 2021, Cites: 7
Improved fisher MAP filter for despeckling of high-resolution SAR images based on structural information detection
Wei W., Sun Z.-G., Zhang Z.-H., Scherer R., Damasevicius R., Improved fisher MAP filter for despeckling of high-resolution SAR images based on structural information detection, Journal of Internet Technology, 22, 22, 413-421, 2021, Cites: 6
Design and implementation of autonomous path planning for intelligent vehicle
Wei W., Gao F., Scherer R., Damasevicius R., Polap D., Design and implementation of autonomous path planning for intelligent vehicle, Journal of Internet Technology, 22, 22, 957-965, 2021, Cites: 5
Traffic flow prediction based on BP neural network
Wang T., Zhang B., Wei W., Damasevicius R., Scherer R., Traffic flow prediction based on BP neural network, 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021, 15-19, 2021, Cites: 5
On robustness of camera identification algorithms
Bernacki J., On robustness of camera identification algorithms, Multimedia Tools and Applications, 80, 80, 921-942, 2021, Cites: 5
Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values
Nowicki R.K., Seliga R., elasko D., Hayashi Y., Performance Analysis of Rough Set-Based Hybrid Classification Systems in the Case of Missing Values, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 307-318, 2021, Cites: 5
Bankline detection of GF-3 SAR images based on shearlet
Sun Z., Zhao G., Wozniak M., Scherer R., Damasevicius R., Bankline detection of GF-3 SAR images based on shearlet, PeerJ Computer Science, 7, 7, 2021, Cites: 5
Synthesis of vertically aligned porous silica thin films functionalized by silver ions
Fedorchuk A., Walcarius A., Laskowska M., Vila N., Kowalczyk P., Cpalka K., Laskowski L., Synthesis of vertically aligned porous silica thin films functionalized by silver ions, International Journal of Molecular Sciences, 22, 22, 2021, Cites: 4
Event-Triggered Control for Output Regulation of Probabilistic Logical Systems with Delays
He J., Liu Y., Lu J., Cao J., Rutkowski L., Event-Triggered Control for Output Regulation of Probabilistic Logical Systems with Delays, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51, 51, 6842-6851, 2021, Cites: 4
A diversified shared latent variable model for efficient image characteristics extraction and modelling
Xiong H., Tang Y.Y., Murtagh F., Rutkowski L., Berkovsky S., A diversified shared latent variable model for efficient image characteristics extraction and modelling, Neurocomputing, 421, 421, 244-259, 2021, Cites: 4
Research on Decision Tree Based on Rough Set
Wei W., Hui M., Zhang B., Scherer R., Damasevicius R., Research on Decision Tree Based on Rough Set, Journal of Internet Technology, 22, 22, 1385-1394, 2021, Cites: 4
Design and implementation of public opinion monitoring system based on cloud platform
Wei W., Wang L., Li X., Zhang B., Scherer R., Design and implementation of public opinion monitoring system based on cloud platform, Journal of Internet Technology, 22, 22, 569-581, 2021, Cites: 3
Human segmentation and tracking survey on masks for mads dataset
Le V.-H., Scherer R., Human segmentation and tracking survey on masks for mads dataset, Sensors, 21, 21, 2021, Cites: 3
Modification of Learning Feedforward Neural Networks with the BP Method
Bilski J., Smolag J., Najgebauer P., Modification of Learning Feedforward Neural Networks with the BP Method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 54-65, 2021, Cites: 2
Handwritten word recognition using fuzzy matching degrees
Wrobel M., Starczewski J.T., Fijalkowska J., Siwocha A., Napoli C., Handwritten word recognition using fuzzy matching degrees, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 229-242, 2021, Cites: 2
Monitoring of Changes in Data Stream Distribution Using Convolutional Restricted Boltzmann Machines
Jaworski M., Rutkowski L., Staszewski P., Najgebauer P., Monitoring of Changes in Data Stream Distribution Using Convolutional Restricted Boltzmann Machines, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 338-346, 2021, Cites: 2
Design of a MEMS sensor array for dam subsidence monitoring based on dual-sensor cooperative measurements
Tao T., Yang J., Wei W., Wozniak M., Scherer R., Damasevicius R., Design of a MEMS sensor array for dam subsidence monitoring based on dual-sensor cooperative measurements, KSII Transactions on Internet and Information Systems, 15, 15, 3554-3570, 2021, Cites: 2
Grid-Based Concise Hash for Solar Images
Grycuk R., Scherer R., Grid-Based Concise Hash for Solar Images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12744 LNCS, 12744 LNCS, 242-254, 2021, Cites: 2
Design and Implementation of Regional Food Distribution Platform Based on Big Data
Wei W., Liang H., Zhang B., Damasevicius R., Scherer R., Design and Implementation of Regional Food Distribution Platform Based on Big Data, 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021, 496-501, 2021, Cites: 2
Application of a Neural Network to Generate the Hash Code for a Device Fingerprint
Gabryel M., Kocic M., Application of a Neural Network to Generate the Hash Code for a Device Fingerprint, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, 456-463, 2021, Cites: 1
Solar Image Hashing by Intermediate Descriptor and Autoencoder
Grycuk R., Scherer R., Solar Image Hashing by Intermediate Descriptor and Autoencoder, Proceedings of the International Joint Conference on Neural Networks, 2021-July, 2021-July, 2021, Cites: 1
A new approach to detection of changes in multidimensional patterns
Galkowski T., Krzyzak A., Patora-Wysocka Z., Filutowicz Z., Wang L., A new approach to detection of changes in multidimensional patterns, Journal of Artificial Intelligence and Soft Computing Research, 11, 11, 217-227, 2021, Cites: 1
Apple Packaging Redesign in LuochuanBased on the Concept of Sustainable Packaging
Ding X., Wei W., Zhang B., Scherer R., Damasevicius R., Apple Packaging Redesign in LuochuanBased on the Concept of Sustainable Packaging, 2021 IEEE International Conference on Artificial Intelligence and Industrial Design, AIID 2021, 614-627, 2021, Cites: 1
Vicinity-Based Abstraction: VA-DGCNN Architecture for Noisy 3D Indoor Object Classification
Walczak J., Wojciechowski A., Najgebauer P., Scherer R., Vicinity-Based Abstraction: VA-DGCNN Architecture for Noisy 3D Indoor Object Classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12744 LNCS, 12744 LNCS, 229-241, 2021, Cites: 1
A low-dimensional layout of magnetic units as nano-systems of combinatorial logic: Numerical simulations
Kuzma D., Kowalczyk P., Cpalka K., Laskowski L., A low-dimensional layout of magnetic units as nano-systems of combinatorial logic: Numerical simulations, Materials, 14, 14, 2021, Cites: 1
Population Management Approaches in the OPn Algorithm
Lapa K., Cpalka K., Slowik A., Population Management Approaches in the OPn Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 402-414, 2021, Cites: 1
A New Variant of the GQR Algorithm for Feedforward Neural Networks Training
Bilski J., Kowalczyk B., A New Variant of the GQR Algorithm for Feedforward Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 41-53, 2021, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, v-vi, 2021, Cites: 0
Sufficient conditions analysis of coverage algorithm constructed positive definite tridiagonal matrices in WSNs
Wei W., Ke Q., Gao F., Scherer R., Fan S., Sufficient conditions analysis of coverage algorithm constructed positive definite tridiagonal matrices in WSNs, Journal of Internet Technology, 22, 22, 735-741, 2021, Cites: 0
A New Interval Type-2 Fuzzy PRISM Algorithm
Bartczuk L., A New Interval Type-2 Fuzzy PRISM Algorithm, IEEE International Conference on Fuzzy Systems, 2021-July, 2021-July, 2021, Cites: 0
Fast Imaging Sensor Identification
Bernacki J., Scherer R., Fast Imaging Sensor Identification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12876 LNAI, 12876 LNAI, 572-584, 2021, Cites: 0
A New Statistical Iterative Reconstruction Algorithm for a CT Scanner with Flying Focal Spot
Cierniak R., Pluta P., A New Statistical Iterative Reconstruction Algorithm for a CT Scanner with Flying Focal Spot, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, 431-441, 2021, Cites: 0
The Streaming Approach to Training Restricted Boltzmann Machines
Duda P., Rutkowski L., Woldan P., Najgebauer P., The Streaming Approach to Training Restricted Boltzmann Machines, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 308-317, 2021, Cites: 0
A Novel Approach to Determining the Radius of the Neighborhood Required for the DBSCAN Algorithm
Starczewski A., A Novel Approach to Determining the Radius of the Neighborhood Required for the DBSCAN Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 358-368, 2021, Cites: 0
Abrupt Change Detection by the Nonparametric Approach Based on Orthogonal Series Estimates
Galkowski T., Krzyzak A., Abrupt Change Detection by the Nonparametric Approach Based on Orthogonal Series Estimates, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, 318-327, 2021, Cites: 0
Fingerprint Device Parameter Stability Analysis
Gabryel M., Kocic M., Fingerprint Device Parameter Stability Analysis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, 464-472, 2021, Cites: 0
Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms
Zalasinski M., Niksa-Rynkiewicz T., Cpalka K., Dynamic Signature Vertical Partitioning Using Selected Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12855 LNAI, 12855 LNAI, 511-518, 2021, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12854 LNAI, 12854 LNAI, v-vi, 2021, Cites: 0

2020 (107)

Multimodal brain tumor classification using deep learning and robust feature selection: A machine learning application for radiologists
Khan M.A., Ashraf I., Alhaisoni M., Damasevicius R., Scherer R., Rehman A., Bukhari S.A.C., Multimodal brain tumor classification using deep learning and robust feature selection: A machine learning application for radiologists, Diagnostics, 10, 10, 2020, Cites: 262
Accurate and fast URL phishing detector: A convolutional neural network approach
Wei W., Ke Q., Nowak J., Korytkowski M., Scherer R., Wozniak M., Accurate and fast URL phishing detector: A convolutional neural network approach, Computer Networks, 178, 178, 2020, Cites: 126
Synchronization of Coupled Time-Delay Neural Networks with Mode-Dependent Average Dwell Time Switching
Yang X., Liu Y., Cao J., Rutkowski L., Synchronization of Coupled Time-Delay Neural Networks with Mode-Dependent Average Dwell Time Switching, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 5483-5496, 2020, Cites: 96
Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach
Liu Y., Zheng Y., Lu J., Cao J., Rutkowski L., Constrained Quaternion-Variable Convex Optimization: A Quaternion-Valued Recurrent Neural Network Approach, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 1022-1035, 2020, Cites: 84
Pearson correlation-based feature selection for document classification using balanced training
Nasir I.M., Khan M.A., Yasmin M., Shah J.H., Gabryel M., Scherer R., Damasevicius R., Pearson correlation-based feature selection for document classification using balanced training, Sensors (Switzerland), 20, 20, 1-18, 2020, Cites: 70
A New Hybrid Particle Swarm Optimization and Genetic Algorithm Method Controlled by Fuzzy Logic
Dziwinski P., Bartczuk L., A New Hybrid Particle Swarm Optimization and Genetic Algorithm Method Controlled by Fuzzy Logic, IEEE Transactions on Fuzzy Systems, 28, 28, 1140-1154, 2020, Cites: 69
Anti-synchronization in fixed time for discontinuous reaction-diffusion neural networks with time-varying coefficients and time delay
Wang Z., Cao J., Cai Z., Rutkowski L., Anti-synchronization in fixed time for discontinuous reaction-diffusion neural networks with time-varying coefficients and time delay, IEEE Transactions on Cybernetics, 50, 50, 2758-2769, 2020, Cites: 67
Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks
Bilski J., Kowalczyk B., Marchlewska A., Zurada J.M., Local Levenberg-Marquardt Algorithm for Learning Feedforwad Neural Networks, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 299-316, 2020, Cites: 64
Distributed Dynamic Self-Triggered Control for Uncertain Complex Networks with Markov Switching Topologies and Random Time-Varying Delay
Tan X., Cao J., Rutkowski L., Distributed Dynamic Self-Triggered Control for Uncertain Complex Networks with Markov Switching Topologies and Random Time-Varying Delay, IEEE Transactions on Network Science and Engineering, 7, 7, 1111-1120, 2020, Cites: 62
Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks
Lin L., Cao J., Rutkowski L., Robust Event-Triggered Control Invariance of Probabilistic Boolean Control Networks, IEEE Transactions on Neural Networks and Learning Systems, 31, 31, 1060-1065, 2020, Cites: 39
A New Method for Automatic Determining of the DBSCAN Parameters
Starczewski A., Goetzen P., Er M.J., A New Method for Automatic Determining of the DBSCAN Parameters, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 209-221, 2020, Cites: 38
Modified Harris Hawks optimizer for solving machine scheduling problems
Jouhari H., Lei D., Al-qaness M.A.A., Abd Elaziz M., Damasevicius R., Korytkowski M., Ewees A.A., Modified Harris Hawks optimizer for solving machine scheduling problems, Symmetry, 12, 12, 2020, Cites: 33
Sampled-Data Set Stabilization of Impulsive Boolean Networks Based on a Hybrid Index Model
Lin L., Cao J., Zhu S., Rutkowski L., Lu G., Sampled-Data Set Stabilization of Impulsive Boolean Networks Based on a Hybrid Index Model, IEEE Transactions on Control of Network Systems, 7, 7, 1859-1869, 2020, Cites: 30
Asymptotic Output Tracking of Probabilistic Boolean Control Networks
Chen B., Cao J., Luo Y., Rutkowski L., Asymptotic Output Tracking of Probabilistic Boolean Control Networks, IEEE Transactions on Circuits and Systems I: Regular Papers, 67, 67, 2780-2790, 2020, Cites: 28
Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic
Korytkowski M., Senkerik R., Scherer M.M., Angryk R.A., Kordos M., Siwocha A., Efficient Image Retrieval by Fuzzy Rules from Boosting and Metaheuristic, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 57-69, 2020, Cites: 26
On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification
Duda P., Rutkowski L., Jaworski M., Rutkowska D., On the Parzen Kernel-Based Probability Density Function Learning Procedures over Time-Varying Streaming Data with Applications to Pattern Classification, IEEE Transactions on Cybernetics, 50, 50, 1683-1696, 2020, Cites: 26
A survey on digital camera identification methods
Bernacki J., A survey on digital camera identification methods, Forensic Science International: Digital Investigation, 34, 34, 2020, Cites: 26
Prediction of streamflow based on dynamic sliding window lstm
Dong L., Fang D., Wang X., Wei W., Damasevicius R., Scherer R., Wozniak M., Prediction of streamflow based on dynamic sliding window lstm, Water (Switzerland), 12, 12, 1-11, 2020, Cites: 24
Lyapunov Functions for the Set Stability and the Synchronization of Boolean Control Networks
Chen B., Cao J., Lu G., Rutkowski L., Lyapunov Functions for the Set Stability and the Synchronization of Boolean Control Networks, IEEE Transactions on Circuits and Systems II: Express Briefs, 67, 67, 2537-2541, 2020, Cites: 22
On Training Deep Neural Networks Using a Streaming Approach
Duda P., Jaworski M., Cader A., Wang L., On Training Deep Neural Networks Using a Streaming Approach, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 15-26, 2020, Cites: 22
Quality control of the continuous hot pressing process of medium density fiberboard using fuzzy failure mode and effects analysis
Lv Y., Liu Y., Jing W., Wozniak M., Damasevicius R., Scherer R., Wei W., Quality control of the continuous hot pressing process of medium density fiberboard using fuzzy failure mode and effects analysis, Applied Sciences (Switzerland), 10, 10, 2020, Cites: 21
Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays
Li H., Fang J.-A., Li X., Rutkowski L., Huang T., Event-triggered impulsive synchronization of discrete-time coupled neural networks with stochastic perturbations and multiple delays, Neural Networks, 132, 132, 447-460, 2020, Cites: 19
Browser fingerprint coding methods increasing the effectiveness of user identification in the web traffic
Gabryel M., Grzanek K., Hayashi Y., Browser fingerprint coding methods increasing the effectiveness of user identification in the web traffic, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 243-253, 2020, Cites: 19
Basic Concepts of Data Stream Mining
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Data Stream Mining, Studies in Big Data, 56, 56, 13-33, 2020, Cites: 17
Nanocomposite for photonics — Nickel pyrophosphate nanocrystals synthesised in silica nanoreactors
Laskowska M., Kityk I., Pastukh O., Dulski M., Zubko M., Jedryka J., Cpalka K., Zielinski P.M., Laskowski, Nanocomposite for photonics — Nickel pyrophosphate nanocrystals synthesised in silica nanoreactors, Microporous and Mesoporous Materials, 306, 306, 2020, Cites: 17
Triangular Fuzzy-Rough Set Based Fuzzification of Fuzzy Rule-Based Systems
Starczewski J.T., Goetzen P., Napoli C., Triangular Fuzzy-Rough Set Based Fuzzification of Fuzzy Rule-Based Systems, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 271-285, 2020, Cites: 16
A New Auto Adaptive Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm
Dziwinski P., Bartczuk L., Paszkowski J., A New Auto Adaptive Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 95-111, 2020, Cites: 16
Rough Support Vector Machine for Classification with Interval and Incomplete Data
Nowicki R.K., Grzanek K., Hayashi Y., Rough Support Vector Machine for Classification with Interval and Incomplete Data, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 47-56, 2020, Cites: 14
Multipopulation Nature-Inspired Algorithm (MNIA) for the Designing of Interpretable Fuzzy Systems
Slowik A., Cpalka K., Lapa K., Multipopulation Nature-Inspired Algorithm (MNIA) for the Designing of Interpretable Fuzzy Systems, IEEE Transactions on Fuzzy Systems, 28, 28, 1125-1139, 2020, Cites: 13
A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method
Cierniak R., Pluta P., KaAmierczak A., A Practical Statistical Approach to the Reconstruction Problem Using a Single Slice Rebinning Method, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 137-149, 2020, Cites: 12
Automatic exposure algorithms for digital photography
Bernacki J., Automatic exposure algorithms for digital photography, Multimedia Tools and Applications, 79, 79, 12751-12776, 2020, Cites: 12
A New Approach to Detection of Changes in Multidimensional Patterns
Galkowski T., Krzyaak A., Filutowicz Z., A New Approach to Detection of Changes in Multidimensional Patterns, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 125-136, 2020, Cites: 11
Evolutionary Algorithm with a Configurable Search Mechanism
Lapa K., Cpalka K., Laskowski L., Cader A., Zeng Z., Evolutionary Algorithm with a Configurable Search Mechanism, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 151-171, 2020, Cites: 11
Nanostructured silica with anchoring units: The 2D solid solvent for molecules and metal ions
Laskowska M., Pastukh O., Fedorchuk A., Schabikowski M., Kowalczyk P., Zalasinski M., Laskowski L., Nanostructured silica with anchoring units: The 2D solid solvent for molecules and metal ions, International Journal of Molecular Sciences, 21, 21, 1-38, 2020, Cites: 11
Detecting Visual Objects by Edge Crawling
Grycuk R., Wojciechowski A., Wei W., Siwocha A., Detecting Visual Objects by Edge Crawling, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 223-237, 2020, Cites: 10
On-Line Signature Partitioning Using a Population Based Algorithm
Zalasinski M., Lapa K., Cpalka K., Przybyszewski K., Yen G.G., On-Line Signature Partitioning Using a Population Based Algorithm, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 5-13, 2020, Cites: 10
Fast Image Index for Database Management Engines
Grycuk R., Najgebauer P., Kordos M., Scherer M.M., Marchlewska A., Fast Image Index for Database Management Engines, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 113-123, 2020, Cites: 10
Concept Drift Detection Using Autoencoders in Data Streams Processing
Jaworski M., Rutkowski L., Angelov P., Concept Drift Detection Using Autoencoders in Data Streams Processing, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 124-133, 2020, Cites: 10
Magnetic behaviour of Mn<inf>12</inf>-stearate single-molecule magnets immobilized on the surface of 300 nm spherical silica nanoparticles
Laskowska M., Pastukh O., Konieczny P., Dulski M., Zalsinski M., Laskowski L., Magnetic behaviour of Mn<inf>12</inf>-stearate single-molecule magnets immobilized on the surface of 300 nm spherical silica nanoparticles, Materials, 13, 13, 2020, Cites: 9
Encoder-Decoder Based CNN Structure for Microscopic Image Identification
Polap D., Wozniak M., Korytkowski M., Scherer R., Encoder-Decoder Based CNN Structure for Microscopic Image Identification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12532 LNCS, 12532 LNCS, 301-312, 2020, Cites: 8
Decision Trees in Data Stream Mining
Rutkowski L., Jaworski M., Duda P., Decision Trees in Data Stream Mining, Studies in Big Data, 56, 56, 37-50, 2020, Cites: 7
High-resolution SAR image despeckling based on nonlocal means filter and modified AA model
Ke Q., Zeng-Guo S., Liu Y., Wei W., Wozniak M., Scherer R., High-resolution SAR image despeckling based on nonlocal means filter and modified AA model, Security and Communication Networks, 2020, 2020, 2020, Cites: 7
A Novel Drift Detection Algorithm Based on Features' Importance Analysis in a Data Streams Environment
Duda P., Przybyszewski K., Wang L., A Novel Drift Detection Algorithm Based on Features' Importance Analysis in a Data Streams Environment, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 287-298, 2020, Cites: 6
Intelligent recommendation of related items based on naive bayes and collaborative filtering combination model
Wei W., Wang Z., Fu C., Damasevicius R., Scherer R., Wozniak M., Intelligent recommendation of related items based on naive bayes and collaborative filtering combination model, Journal of Physics: Conference Series, 1682, 1682, 2020, Cites: 6
Synthesis in silica nanoreactor: Copper pyrophosphate quantum dots and silver oxide nanocrystallites inside silica mezochannels
Laskowski L., Majtyka-Pilat A., Cpalka K., Zubko M., Laskowska M., Synthesis in silica nanoreactor: Copper pyrophosphate quantum dots and silver oxide nanocrystallites inside silica mezochannels, Materials, 13, 13, 2020, Cites: 5
An Algorithm for the Evolutionary-Fuzzy Generation of on-Line Signature Hybrid Descriptors
Zalasinski M., Cpalka K., Laskowski L., Wunsch D.C., Przybyszewski K., An Algorithm for the Evolutionary-Fuzzy Generation of on-Line Signature Hybrid Descriptors, Journal of Artificial Intelligence and Soft Computing Research, 10, 10, 173-187, 2020, Cites: 5
Efficient visual classification by fuzzy rules
Korytkowski M., Scherer R., Szajerman D., Polap D., Wozniak M., Efficient visual classification by fuzzy rules, IEEE International Conference on Fuzzy Systems, 2020-July, 2020-July, 2020, Cites: 5
Fingerprinting of url logs: Continuous user authentication from behavioural patterns
Nowak J., Holotyak T., Korytkowski M., Scherer R., Voloshynovskiy S., Fingerprinting of url logs: Continuous user authentication from behavioural patterns, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12140 LNCS, 12140 LNCS, 184-195, 2020, Cites: 4
Fast Conjugate Gradient Algorithm for Feedforward Neural Networks
Bilski J., Smolag J., Fast Conjugate Gradient Algorithm for Feedforward Neural Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 27-38, 2020, Cites: 4
Fully Convolutional Network for Removing DCT Artefacts from Images
Najgebauer P., Scherer R., Rutkowski L., Fully Convolutional Network for Removing DCT Artefacts from Images, Proceedings of the International Joint Conference on Neural Networks, 2020, Cites: 4
Ghomr: Multi-receptive lightweight residual modules for hyperspectral classification
Das A., Saha I., Scherer R., Ghomr: Multi-receptive lightweight residual modules for hyperspectral classification, Sensors (Switzerland), 20, 20, 1-19, 2020, Cites: 4
Grid-Based Approach to Determining Parameters of the DBSCAN Algorithm
Starczewski A., Cader A., Grid-Based Approach to Determining Parameters of the DBSCAN Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 555-565, 2020, Cites: 3
Intelligent Approach to the Prediction of Changes in Biometric Attributes
Zalasinski M., Lapa K., Laskowska M., Intelligent Approach to the Prediction of Changes in Biometric Attributes, IEEE Transactions on Fuzzy Systems, 28, 28, 1073-1083, 2020, Cites: 3
A Pilot Study for Investigating Gait Signatures in Multi-Scenario Applications
Hazra S., Roy P., Nandy A., Scherer R., A Pilot Study for Investigating Gait Signatures in Multi-Scenario Applications, Proceedings of the International Joint Conference on Neural Networks, 2020, Cites: 3
Visual Hybrid Recommendation Systems Based on the Content-Based Filtering
Woldan P., Duda P., Hayashi Y., Visual Hybrid Recommendation Systems Based on the Content-Based Filtering, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 455-465, 2020, Cites: 3
Misclassification Error Impurity Measure
Rutkowski L., Jaworski M., Duda P., Misclassification Error Impurity Measure, Studies in Big Data, 56, 56, 63-82, 2020, Cites: 2
Statistical iterative reconstruction algorithm based on a continuous-to-continuous model formulated for spiral cone-beam ct
Cierniak R., Pluta P., Statistical iterative reconstruction algorithm based on a continuous-to-continuous model formulated for spiral cone-beam ct, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12139 LNCS, 12139 LNCS, 613-620, 2020, Cites: 2
FastText and XGBoost Content-Based Classification for Employment Web Scraping
Talun A., Drozda P., Bukowski L., Scherer R., FastText and XGBoost Content-Based Classification for Employment Web Scraping, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 435-444, 2020, Cites: 2
A Novel Explainable Recommender for Investment Managers
Rutkowski T., Nielek R., Rutkowska D., Rutkowski L., A Novel Explainable Recommender for Investment Managers, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 412-422, 2020, Cites: 2
Probabilistic Neural Networks for the Streaming Data Classification
Rutkowski L., Jaworski M., Duda P., Probabilistic Neural Networks for the Streaming Data Classification, Studies in Big Data, 56, 56, 245-277, 2020, Cites: 2
A New Approach to Detection of Abrupt Changes in Black-and-White Images
Galkowski T., Krzyzak A., A New Approach to Detection of Abrupt Changes in Black-and-White Images, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 3-18, 2020, Cites: 2
An interpretable fuzzy system in the on-line signature scalable verification
Zalasinski M., Cpalka K., Lapa K., An interpretable fuzzy system in the on-line signature scalable verification, IEEE International Conference on Fuzzy Systems, 2020-July, 2020-July, 2020, Cites: 2
Grouping Handwritten Letter Strokes Using a Fuzzy Decision Tree
Wrobel M., Starczewski J.T., Napoli C., Grouping Handwritten Letter Strokes Using a Fuzzy Decision Tree, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 103-113, 2020, Cites: 2
Digital camera identification based on analysis of optical defects
Bernacki J., Digital camera identification based on analysis of optical defects, Multimedia Tools and Applications, 79, 79, 2945-2963, 2020, Cites: 2
Visual analysis of computer game output video stream for gameplay metrics
Kozlowski K., Korytkowski M., Szajerman D., Visual analysis of computer game output video stream for gameplay metrics, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12141 LNCS, 12141 LNCS, 538-552, 2020, Cites: 2
Complex systems and networks with their applications
Cao J.-D., Liu Y., Lu J.-Q., Rutkowski L., Complex systems and networks with their applications, Frontiers of Information Technology and Electronic Engineering, 21, 21, 195-198, 2020, Cites: 1
Normal grouping density separation (ngds): A novel object-driven indoor point cloud partition method
Walczak J., Andrzejczak G., Scherer R., Wojciechowski A., Normal grouping density separation (ngds): A novel object-driven indoor point cloud partition method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12142 LNCS, 12142 LNCS, 100-114, 2020, Cites: 1
Explainable Cluster-Based Rules Generation for Image Retrieval and Classification
Staszewski P., Jaworski M., Rutkowski L., Tao D., Explainable Cluster-Based Rules Generation for Image Retrieval and Classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 85-94, 2020, Cites: 1
Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm
Bartczuk L., Dziwinski P., Goetzen P., Nonlinear Fuzzy Modelling of Dynamic Objects with Fuzzy Hybrid Particle Swarm Optimization and Genetic Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 315-325, 2020, Cites: 1
General Non-parametric Learning Procedure for Tracking Concept Drift
Rutkowski L., Jaworski M., Duda P., General Non-parametric Learning Procedure for Tracking Concept Drift, Studies in Big Data, 56, 56, 155-172, 2020, Cites: 1
Novel Fast Binary Hash for Content-based Solar Image Retrieval
Grycuk R., Scherer R., Novel Fast Binary Hash for Content-based Solar Image Retrieval, Proceedings of the International Joint Conference on Neural Networks, 2020, Cites: 1
Cascade PID Controller Optimization Using Bison Algorithm
Kazikova A., Lapa K., Pluhacek M., Senkerik R., Cascade PID Controller Optimization Using Bison Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 406-416, 2020, Cites: 1
Feature detection
Scherer R., Feature detection, Studies in Computational Intelligence, 821, 821, 7-32, 2020, Cites: 1
Online job search and recruitment platform for college students based on SSH
Wei W., Wang B., Zhang B., Scherer R., Damasevicius R., Online job search and recruitment platform for college students based on SSH, Proceedings - 2020 International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2020, 355-358, 2020, Cites: 1
Introduction to the Special Issue on Nature-Inspired Optimization Methods in Fuzzy Systems
Slowik A., Cpalka K., Jin Y., Introduction to the Special Issue on Nature-Inspired Optimization Methods in Fuzzy Systems, IEEE Transactions on Fuzzy Systems, 28, 28, 1019-1022, 2020, Cites: 1
Hybrid Splitting Criteria
Rutkowski L., Jaworski M., Duda P., Hybrid Splitting Criteria, Studies in Big Data, 56, 56, 91-113, 2020, Cites: 1
Image retrieval and classification in relational databases
Scherer R., Image retrieval and classification in relational databases, Studies in Computational Intelligence, 821, 821, 107-136, 2020, Cites: 1
Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks
Rutkowski L., Jaworski M., Duda P., Nonparametric Regression Models for Data Streams Based on the Generalized Regression Neural Networks, Studies in Big Data, 56, 56, 173-244, 2020, Cites: 1
Edge Curve Estimation by the Nonparametric Parzen Kernel Method
Galkowski T., Krzyzak A., Edge Curve Estimation by the Nonparametric Parzen Kernel Method, Communications in Computer and Information Science, 1332, 1332, 377-385, 2020, Cites: 1
The Dynamic Signature Verification Using population-Based Vertical Partitioning
Zalasinski M., Cpalka K., Niksa-Rynkiewicz T., The Dynamic Signature Verification Using population-Based Vertical Partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12532 LNCS, 12532 LNCS, 569-579, 2020, Cites: 1
Discovering Sequential Patterns by Neural Networks
Nowak J., Korytkowski M., Scherer R., Discovering Sequential Patterns by Neural Networks, Proceedings of the International Joint Conference on Neural Networks, 2020, Cites: 1
Introduction and Overview of the Main Results of the Book
Rutkowski L., Jaworski M., Duda P., Introduction and Overview of the Main Results of the Book, Studies in Big Data, 56, 56, 1-10, 2020, Cites: 1
Signature Partitioning Using Selected Population-Based Algorithms
Zalasinski M., Cpalka K., Niksa-Rynkiewicz T., Hayashi Y., Signature Partitioning Using Selected Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 480-488, 2020, Cites: 0
Design and implementation of forward modeling algorithm for anisotropic seismic waves
Wei W., Gao F., Zhang B., Scherer R., Hui M., Damasevicius R., Design and implementation of forward modeling algorithm for anisotropic seismic waves, Proceedings - 2020 International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2020, 341-350, 2020, Cites: 0
Classification
Rutkowski L., Jaworski M., Duda P., Classification, Studies in Big Data, 56, 56, 287-308, 2020, Cites: 0
Methods of Searching for Similar Device Fingerprints Using Changes in Unstable Parameters
Gabryel M., Przybyszewski K., Methods of Searching for Similar Device Fingerprints Using Changes in Unstable Parameters, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 325-335, 2020, Cites: 0
A Population-Based Method with Selection of a Search Operator
Lapa K., Cpalka K., Niksa-Rynkiewicz T., Wang L., A Population-Based Method with Selection of a Search Operator, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 429-444, 2020, Cites: 0
Basic Concepts of Probabilistic Neural Networks
Rutkowski L., Jaworski M., Duda P., Basic Concepts of Probabilistic Neural Networks, Studies in Big Data, 56, 56, 117-154, 2020, Cites: 0
Preface
Scherer R., Preface, Studies in Computational Intelligence, 821, 821, v, 2020, Cites: 0
On a Streaming Approach for Training Denoising Auto-encoders
Duda P., Wang L., On a Streaming Approach for Training Denoising Auto-encoders, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 315-324, 2020, Cites: 0
Splitting Criteria with the Bias Term
Rutkowski L., Jaworski M., Duda P., Splitting Criteria with the Bias Term, Studies in Big Data, 56, 56, 83-89, 2020, Cites: 0
Image indexing techniques
Scherer R., Image indexing techniques, Studies in Computational Intelligence, 821, 821, 33-82, 2020, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, v-vi, 2020, Cites: 0
Active Region-Based Full-Disc Solar Image Hashing
Grycuk R., Costa K., Scherer R., Active Region-Based Full-Disc Solar Image Hashing, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 19-30, 2020, Cites: 0
Educational management system
Wei W., Li X., Zhang B., Liu X., Scherer R., Damasevicius R., Educational management system, Proceedings - 2020 International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2020, 53-56, 2020, Cites: 0
A New Algorithm with a Line Search for Feedforward Neural Networks Training
Bilski J., Kowalczyk B., Zurada J.M., A New Algorithm with a Line Search for Feedforward Neural Networks Training, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, 15-26, 2020, Cites: 0
Concluding remarks and perspectives in computer vision
Scherer R., Concluding remarks and perspectives in computer vision, Studies in Computational Intelligence, 821, 821, 137, 2020, Cites: 0
The General Procedure of Ensembles Construction in Data Stream Scenarios
Rutkowski L., Jaworski M., Duda P., The General Procedure of Ensembles Construction in Data Stream Scenarios, Studies in Big Data, 56, 56, 281-286, 2020, Cites: 0
Novel methods for image description
Scherer R., Novel methods for image description, Studies in Computational Intelligence, 821, 821, 83-105, 2020, Cites: 0
Job Offer Analysis Using Convolutional and Recurrent Convolutional Networks
Nowak J., Milkowska K., Scherer M., Talun A., Korytkowski M., Job Offer Analysis Using Convolutional and Recurrent Convolutional Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12416 LNAI, 12416 LNAI, 380-387, 2020, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12415 LNAI, 12415 LNAI, v-vi, 2020, Cites: 0
SmartX – IoT MANAGEMENT PLATFORM
Kowalczyk B., Szelag P., SmartX – IoT MANAGEMENT PLATFORM, Rynek Energii, 2020, 2020, 54-60, 2020, Cites: 0
Regression
Rutkowski L., Jaworski M., Duda P., Regression, Studies in Big Data, 56, 56, 309-322, 2020, Cites: 0
Research on variable scale algorithm
Wei W., Hui M., Zhang B., Scherer R., Gao F., Damasevicius R., Research on variable scale algorithm, Proceedings - 2020 International Conference on Intelligent Computing and Human-Computer Interaction, ICHCI 2020, 316-322, 2020, Cites: 0
Introduction
Scherer R., Introduction, Studies in Computational Intelligence, 821, 821, 1-5, 2020, Cites: 0
Final Remarks and Challenging Problems
Rutkowski L., Jaworski M., Duda P., Final Remarks and Challenging Problems, Studies in Big Data, 56, 56, 323-327, 2020, Cites: 0
Splitting Criteria Based on the McDiarmid’s Theorem
Rutkowski L., Jaworski M., Duda P., Splitting Criteria Based on the McDiarmid’s Theorem, Studies in Big Data, 56, 56, 51-62, 2020, Cites: 0

2019 (47)

HEMIGEN: Human embryo image generator based on generative adversarial networks
Dirvanauskas D., Maskeliunas R., Raudonis V., Damasevicius R., Scherer R., HEMIGEN: Human embryo image generator based on generative adversarial networks, Sensors (Switzerland), 19, 19, 2019, Cites: 35
On Explainable Fuzzy Recommenders and their Performance Evaluation
Rutkowski T., Lapa K., Nielek R., On Explainable Fuzzy Recommenders and their Performance Evaluation, International Journal of Applied Mathematics and Computer Science, 29, 29, 595-610, 2019, Cites: 21
Inertia-based Fast Vectorization of Line Drawings
Najgebauer P., Scherer R., Inertia-based Fast Vectorization of Line Drawings, Computer Graphics Forum, 38, 38, 203-213, 2019, Cites: 14
Determining the eps parameter of the DBSCAN algorithm
Starczewski A., Cader A., Determining the eps parameter of the DBSCAN algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 420-430, 2019, Cites: 13
On explainable flexible fuzzy recommender and its performance evaluation using the akaike information criterion
Rutkowski T., Lapa K., Jaworski M., Nielek R., Rutkowska D., On explainable flexible fuzzy recommender and its performance evaluation using the akaike information criterion, Communications in Computer and Information Science, 1142 CCIS, 1142 CCIS, 717-724, 2019, Cites: 12
Meta-optimization of multi-objective population-based algorithms using multi-objective performance metrics
Lapa K., Meta-optimization of multi-objective population-based algorithms using multi-objective performance metrics, Information Sciences, 489, 489, 193-204, 2019, Cites: 11
On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques
Rutkowski T., Lapa K., Nowicki R., Nielek R., Grzanek K., On Explainable Recommender Systems Based on Fuzzy Rule Generation Techniques, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 358-372, 2019, Cites: 7
A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm
Dziwinski P., Bartczuk L., Goetzen P., A New Hybrid Particle Swarm Optimization and Evolutionary Algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 432-444, 2019, Cites: 6
The dynamically modified BoW algorithm used in assessing clicks in online ads
Gabryel M., Przybyszewski K., The dynamically modified BoW algorithm used in assessing clicks in online ads, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 350-360, 2019, Cites: 6
Algorithm Based on Population with a Flexible Search Mechanism
Lapa K., Cpalka K., Zalasinski M., Algorithm Based on Population with a Flexible Search Mechanism, IEEE Access, 7, 7, 132253-132270, 2019, Cites: 5
Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection
Najgebauer P., Grycuk R., Rutkowski L., Scherer R., Siwocha A., Microscopic Sample Segmentation by Fully Convolutional Network for Parasite Detection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 164-171, 2019, Cites: 4
Resource-aware data stream mining using the restricted boltzmann machine
Jaworski M., Rutkowski L., Duda P., Cader A., Resource-aware data stream mining using the restricted boltzmann machine, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 384-396, 2019, Cites: 4
Distributed image retrieval with colour and keypoint features
Lagiewka M., Korytkowski M., Scherer R., Distributed image retrieval with colour and keypoint features, Journal of Information and Telecommunication, 3, 3, 430-445, 2019, Cites: 4
Rough Fuzzy Classification Systems
Nowicki R.K., Rough Fuzzy Classification Systems, Studies in Computational Intelligence, 802, 802, 17-70, 2019, Cites: 3
Hybrid Multi-population Based Approach for Controllers Structure and Parameters Selection
Lapa K., Cpalka K., Paszkowski J., Hybrid Multi-population Based Approach for Controllers Structure and Parameters Selection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 456-468, 2019, Cites: 3
The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms
Zalasinski M., Lapa K., Cpalka K., Marchlewska A., The Method of Predicting Changes of a Dynamic Signature Using Possibilities of Population-Based Algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 540-549, 2019, Cites: 2
Environment scene classification based on images using bag-of-words
Petraitis T., Maskeliunas R., Damasevicius R., Polap D., Wozniak M., Gabryel M., Environment scene classification based on images using bag-of-words, Studies in Computational Intelligence, 829, 829, 281-303, 2019, Cites: 2
Exponential Stabilization for Hybrid Recurrent Neural Networks by Delayed Noises Rooted in Discrete Observations of State and Mode
Feng L., Cao J., Hu J., Wu Z., Rutkowski L., Exponential Stabilization for Hybrid Recurrent Neural Networks by Delayed Noises Rooted in Discrete Observations of State and Mode, Neural Processing Letters, 50, 50, 2797-2819, 2019, Cites: 2
Software framework for fast image retrieval
Grycuk R., Scherer R., Software framework for fast image retrieval, 2019 24th International Conference on Methods and Models in Automation and Robotics, MMAR 2019, 588-593, 2019, Cites: 2
A greedy algorithm for extraction of handwritten strokes
Wrobel M., Starczewski J.T., Nieszporek K., Opielka P., Kazmierczak A., A greedy algorithm for extraction of handwritten strokes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 464-473, 2019, Cites: 2
Rough Nearest Neighbour Classifier
Nowicki R.K., Rough Nearest Neighbour Classifier, Studies in Computational Intelligence, 802, 802, 133-159, 2019, Cites: 2
Fuzzy-rough fuzzification in general FL classifiers
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy-rough fuzzification in general FL classifiers, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 335-342, 2019, Cites: 2
On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine
Jaworski M., Duda P., Rutkowska D., Rutkowski L., On Handling Missing Values in Data Stream Mining Algorithms Based on the Restricted Boltzmann Machine, Communications in Computer and Information Science, 1143 CCIS, 1143 CCIS, 347-354, 2019, Cites: 2
Rough Set Theory Fundamentals
Nowicki R.K., Rough Set Theory Fundamentals, Studies in Computational Intelligence, 802, 802, 7-16, 2019, Cites: 2
Convolutional Recurrent Neural Networks for Computer Network Analysis
Nowak J., Korytkowski M., Scherer R., Convolutional Recurrent Neural Networks for Computer Network Analysis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11730 LNCS, 11730 LNCS, 747-757, 2019, Cites: 1
On the hermite series-based generalized regression neural networks for stream data mining
Rutkowska D., Rutkowski L., On the hermite series-based generalized regression neural networks for stream data mining, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11955 LNCS, 11955 LNCS, 437-448, 2019, Cites: 1
Application of Spiking Neural Networks to Fashion Classification
Opielka P., Starczewski J.T., Wrobel M., Nieszporek K., Marchlewska A., Application of Spiking Neural Networks to Fashion Classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 172-180, 2019, Cites: 1
Multilayer architecture for content-based image retrieval systems
Grycuk R., Najgebauer P., Nowicki R., Scherer R., Multilayer architecture for content-based image retrieval systems, Proceedings - 2019 IEEE 12th Conference on Service-Oriented Computing and Applications, SOCA 2019, 119-126, 2019, Cites: 1
Extended possibilistic fuzzification for classification
Nowicki R.K., Starczewski J.T., Grycuk R., Extended possibilistic fuzzification for classification, IJCCI 2019 - Proceedings of the 11th International Joint Conference on Computational Intelligence, 343-350, 2019, Cites: 1
Final Remarks
Nowicki R.K., Final Remarks, Studies in Computational Intelligence, 802, 802, 185-188, 2019, Cites: 0
Rough Neural Network Classifier
Nowicki R.K., Rough Neural Network Classifier, Studies in Computational Intelligence, 802, 802, 95-132, 2019, Cites: 0
Iterative Statistical Reconstruction Algorithm Based on C-C Data Model with the Direct Use of Projections Performed in Spiral Cone-Beam CT Scanners
Cierniak R., Pluta P., Iterative Statistical Reconstruction Algorithm Based on C-C Data Model with the Direct Use of Projections Performed in Spiral Cone-Beam CT Scanners, Advances in Intelligent Systems and Computing, 1011, 1011, 56-66, 2019, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, v-vi, 2019, Cites: 0
Ensembles of Rough Set–Based Classifiers
Nowicki R.K., Ensembles of Rough Set–Based Classifiers, Studies in Computational Intelligence, 802, 802, 161-184, 2019, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, v-vi, 2019, Cites: 0
On Proper Designing of Deep Structures for Image Classification
Woldan P., Staszewski P., Rutkowski L., Grzanek K., On Proper Designing of Deep Structures for Image Classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 223-235, 2019, Cites: 0
Sequential Data Mining of Network Traffic in URL Logs
Korytkowski M., Nowak J., Nowicki R., Milkowska K., Scherer M., Goetzen P., Sequential Data Mining of Network Traffic in URL Logs, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 125-130, 2019, Cites: 0
Extended Possibilistic Fuzzification for Classification
Nowicki R.K., Starczewski J.T., Grycuk R., Extended Possibilistic Fuzzification for Classification, International Joint Conference on Computational Intelligence, 1, 1, 343-350, 2019, Cites: 0
Modifications of the Givens Training Algorithm for Artificial Neural Networks
Bilski J., Kowalczyk B., Cader A., Modifications of the Givens Training Algorithm for Artificial Neural Networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11508 LNAI, 11508 LNAI, 14-28, 2019, Cites: 0
Fuzzy–rough Fuzzification in General FL Classifiers
Starczewski J.T., Nowicki R.K., Nieszporek K., Fuzzy–rough Fuzzification in General FL Classifiers, International Joint Conference on Computational Intelligence, 1, 1, 335-342, 2019, Cites: 0
Realizations of the statistical reconstruction method based on the continuous-to-continuous data model
Cierniak R., Bilski J., Pluta P., Filutowicz Z., Realizations of the statistical reconstruction method based on the continuous-to-continuous data model, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 149-156, 2019, Cites: 0
Introduction
Nowicki R.K., Introduction, Studies in Computational Intelligence, 802, 802, 1-6, 2019, Cites: 0
A new concept of nonparametric kernel approach for edge detection
Galkowski T., Przybyszewski K., A new concept of nonparametric kernel approach for edge detection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11509 LNAI, 11509 LNAI, 361-370, 2019, Cites: 0
SEARCHING THE BEGINNING OF THE CLIMB TO GET THE MOST RELIABLE DIFFICULTY INDEX
Wrobel M., SEARCHING THE BEGINNING OF THE CLIMB TO GET THE MOST RELIABLE DIFFICULTY INDEX, Journal of Applied Mathematics and Computational Mechanics, 18, 18, 97-103, 2019, Cites: 0
Fuzzy Rough Classification Systems
Nowicki R.K., Fuzzy Rough Classification Systems, Studies in Computational Intelligence, 802, 802, 71-93, 2019, Cites: 0
EM-ML algorithm based on continuous-to-continuous model for PET
Cierniak R., Dobosz P., Grzybowski A., EM-ML algorithm based on continuous-to-continuous model for PET, Proceedings of SPIE - The International Society for Optical Engineering, 11072, 11072, 2019, Cites: 0
Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028))
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., Corrigendum to ‘How to adjust an ensemble size in stream data mining?’ (Information Sciences (2017) 381 (46–54), (S0020025516313445) (10.1016/j.ins.2016.10.028)), Information Sciences, 477, 477, 545, 2019, Cites: 0

2018 (43)

New Splitting Criteria for Decision Trees in Stationary Data Streams
Jaworski M., Duda P., Rutkowski L., New Splitting Criteria for Decision Trees in Stationary Data Streams, IEEE Transactions on Neural Networks and Learning Systems, 29, 29, 2516-2529, 2018, Cites: 83
A content-based recommendation system using neuro-fuzzy approach
Rutkowski T., Romanowski J., Woldan P., Staszewski P., Nielek R., Rutkowski L., A content-based recommendation system using neuro-fuzzy approach, IEEE International Conference on Fuzzy Systems, 2018-July, 2018-July, 2018, Cites: 47
Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks
Duda P., Jaworski M., Rutkowski L., Convergent Time-Varying Regression Models for Data Streams: Tracking Concept Drift by the Recursive Parzen-Based Generalized Regression Neural Networks, International Journal of Neural Systems, 28, 28, 2018, Cites: 30
Flexible Fuzzy PID Controller (FFPIDC) and a Nature-Inspired Method for Its Construction
Lapa K., Cpalka K., Flexible Fuzzy PID Controller (FFPIDC) and a Nature-Inspired Method for Its Construction, IEEE Transactions on Industrial Informatics, 14, 14, 1078-1088, 2018, Cites: 27
Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks
Duda P., Jaworski M., Rutkowski L., Knowledge discovery in data streams with the orthogonal series-based generalized regression neural networks, Information Sciences, 460-461, 460-461, 497-518, 2018, Cites: 24
Genetic programming algorithm for designing of control systems
Lapa K., Cpalka K., Przybyl A., Genetic programming algorithm for designing of control systems, Information Technology and Control, 47, 47, 668-683, 2018, Cites: 17
Prediction of values of the dynamic signature features
Zalasinski M., Lapa K., Cpalka K., Prediction of values of the dynamic signature features, Expert Systems with Applications, 104, 104, 86-96, 2018, Cites: 17
Data Analysis Algorithm for Click Fraud Recognition
Gabryel M., Data Analysis Algorithm for Click Fraud Recognition, Communications in Computer and Information Science, 920, 920, 437-446, 2018, Cites: 15
New aspects of interpretability of fuzzy systems for nonlinear modeling
Lapa K., Cpalka K., Rutkowski L., New aspects of interpretability of fuzzy systems for nonlinear modeling, Studies in Computational Intelligence, 738, 738, 225-264, 2018, Cites: 14
The bag-of-words method with different types of image features and dictionary analysis
Gabryel M., The bag-of-words method with different types of image features and dictionary analysis, Journal of Universal Computer Science, 24, 24, 357-371, 2018, Cites: 13
Application of the bag-of-words algorithm in classification the quality of sales leads
Gabryel M., Damasevicius R., Przybyszewski K., Application of the bag-of-words algorithm in classification the quality of sales leads, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 615-622, 2018, Cites: 13
Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine
Jaworski M., Duda P., Rutkowski L., Concept Drift Detection in Streams of Labelled Data Using the Restricted Boltzmann Machine, Proceedings of the International Joint Conference on Neural Networks, 2018-July, 2018-July, 2018, Cites: 13
Multi-objective evolutionary instance selection for regression tasks
Kordos M., Lapa K., Multi-objective evolutionary instance selection for regression tasks, Entropy, 20, 20, 2018, Cites: 12
A new method for signature verification based on selection of the most important partitions of the dynamic signature
Zalasinski M., Cpalka K., A new method for signature verification based on selection of the most important partitions of the dynamic signature, Neurocomputing, 289, 289, 13-22, 2018, Cites: 11
Random forests for profiling computer network users
Nowak J., Korytkowski M., Nowicki R., Scherer R., Siwocha A., Random forests for profiling computer network users, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 734-739, 2018, Cites: 11
The parallel modification to the levenberg-marquardt algorithm
Bilski J., Kowalczyk B., Grzanek K., The parallel modification to the levenberg-marquardt algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 15-24, 2018, Cites: 10
Negative space-based population initialization algorithm (NSPIA)
Lapa K., Cpalka K., Przybyl A., Grzanek K., Negative space-based population initialization algorithm (NSPIA), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 449-461, 2018, Cites: 8
Fuzzy-genetic approach to identity verification using a handwritten signature
Zalasinski M., Cpalka K., Rutkowski L., Fuzzy-genetic approach to identity verification using a handwritten signature, Studies in Computational Intelligence, 738, 738, 375-394, 2018, Cites: 6
Hard real-time communication solution for mechatronic systems
Przybyl A., Hard real-time communication solution for mechatronic systems, Robotics and Computer-Integrated Manufacturing, 49, 49, 309-316, 2018, Cites: 6
Online grnn-based ensembles for regression on evolving data streams
Duda P., Jaworski M., Rutkowski L., Online grnn-based ensembles for regression on evolving data streams, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10878 LNCS, 10878 LNCS, 221-228, 2018, Cites: 6
A fuzzy measure for recognition of handwritten letter strokes
Wrobel M., Nieszporek K., Starczewski J.T., Cader A., A fuzzy measure for recognition of handwritten letter strokes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 761-770, 2018, Cites: 6
A fuzzy SOM for understanding incomplete 3D faces
Starczewski J.T., Nieszporek K., Wrobel M., Grzanek K., A fuzzy SOM for understanding incomplete 3D faces, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 73-80, 2018, Cites: 4
A population based algorithm and fuzzy decision trees for nonlinear modeling
Dziwinski P., Bartczuk L., Przybyszewski K., A population based algorithm and fuzzy decision trees for nonlinear modeling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 516-531, 2018, Cites: 4
Rough neural network ensemble for interval data classification
Nowicki R.K., Korytkowski M., Scherer R., Rough neural network ensemble for interval data classification, IEEE International Conference on Fuzzy Systems, 2018-July, 2018-July, 2018, Cites: 3
A method for genetic selection of the dynamic signature global features’ subset
Zalasinski M., Cpalka K., A method for genetic selection of the dynamic signature global features’ subset, Advances in Intelligent Systems and Computing, 655, 655, 73-82, 2018, Cites: 3
Obtaining pareto front in instance selection with ensembles and populations
Kordos M., Wydrzynski M., Lapa K., Obtaining pareto front in instance selection with ensembles and populations, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 438-448, 2018, Cites: 3
Classification of computer network users with convolutional neural networks
Nowak J., Korytkowski M., Scherer R., Classification of computer network users with convolutional neural networks, Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, FedCSIS 2018, 501-504, 2018, Cites: 3
On ensemble components selection in data streams scenario with gradual concept-drift
Duda P., On ensemble components selection in data streams scenario with gradual concept-drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 311-320, 2018, Cites: 3
Fast Two-Level Image Indexing Based on Local Interest Points
Najgebauer P., Grycuk R., Scherer R., Fast Two-Level Image Indexing Based on Local Interest Points, 2018 23rd International Conference on Methods and Models in Automation and Robotics, MMAR 2018, 613-617, 2018, Cites: 2
Architecture of database index for content-based image retrieval systems
Grycuk R., Najgebauer P., Scherer R., Siwocha A., Architecture of database index for content-based image retrieval systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 36-47, 2018, Cites: 1
On the global convergence of the parzen-based generalized regression neural networks applied to streaming data
Cao J., Rutkowski L., On the global convergence of the parzen-based generalized regression neural networks applied to streaming data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, 25-34, 2018, Cites: 1
Evolutionary approach for automatic design of PID controllers
Lapa K., Cpalka K., Evolutionary approach for automatic design of PID controllers, Studies in Computational Intelligence, 738, 738, 353-373, 2018, Cites: 1
Improvement of the simplified silhouette validity index
Starczewski A., Przybyszewski K., Improvement of the simplified silhouette validity index, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 433-444, 2018, Cites: 1
Estimation of probability density function, differential entropy and other relative quantities for data streams with concept drift
Jaworski M., Najgebauer P., Goetzen P., Estimation of probability density function, differential entropy and other relative quantities for data streams with concept drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 376-386, 2018, Cites: 1
PID-fuzzy controllers with dynamic structure and evolutionary method for their construction
Lapa K., Cpalka K., PID-fuzzy controllers with dynamic structure and evolutionary method for their construction, Advances in Intelligent Systems and Computing, 655, 655, 138-148, 2018, Cites: 1
Symbolic regression with the AMSTA+GP in a non-linear modelling of dynamic objects
Bartczuk L., Dziwinski P., Cader A., Symbolic regression with the AMSTA+GP in a non-linear modelling of dynamic objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 504-515, 2018, Cites: 0
Stability of features describing the dynamic signature biometric attribute
Zalasinski M., Cpalka K., Grzanek K., Stability of features describing the dynamic signature biometric attribute, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 250-261, 2018, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, V-VI, 2018, Cites: 0
Population-based algorithm with selectable evolutionary operators for nonlinear modeling
Lapa K., Population-based algorithm with selectable evolutionary operators for nonlinear modeling, Advances in Intelligent Systems and Computing, 655, 655, 15-26, 2018, Cites: 0
Performance evaluation of DBN learning on intel multi- and manycore architectures
Olas T., Mleczko W.K., Wozniak M., Nowicki R.K., Gepner P., Performance evaluation of DBN learning on intel multi- and manycore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10777 LNCS, 10777 LNCS, 565-575, 2018, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10841 LNAI, 10841 LNAI, V-VI, 2018, Cites: 0
Outliers detection in regressions by nonparametric parzen kernel estimation
Galkowski T., Cader A., Outliers detection in regressions by nonparametric parzen kernel estimation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 354-363, 2018, Cites: 0
Analytical realization of the EM algorithm for emission positron tomography
Cierniak R., Dobosz P., Pluta P., Filutowicz P., Analytical realization of the EM algorithm for emission positron tomography, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10842 LNAI, 10842 LNAI, 127-136, 2018, Cites: 0

2017 (51)

LSTM recurrent neural networks for short text and sentiment classification
Nowak J., Taspinar A., Scherer R., LSTM recurrent neural networks for short text and sentiment classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 553-562, 2017, Cites: 116
How to adjust an ensemble size in stream data mining?
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., How to adjust an ensemble size in stream data mining?, Information Sciences, 381, 381, 46-54, 2017, Cites: 61
A new validity index for crisp clusters
Starczewski A., A new validity index for crisp clusters, Pattern Analysis and Applications, 20, 20, 687-700, 2017, Cites: 47
The image classification with different types of image features
Gabryel M., Damasevicius R., The image classification with different types of image features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 497-506, 2017, Cites: 33
A new method for classification of imprecise data using fuzzy rough fuzzification
Nowicki R.K., Starczewski J.T., A new method for classification of imprecise data using fuzzy rough fuzzification, Information Sciences, 414, 414, 33-52, 2017, Cites: 25
Novel visual information indexing in relational databases
Korytkowski M., Novel visual information indexing in relational databases, Integrated Computer-Aided Engineering, 24, 24, 119-128, 2017, Cites: 16
Handwriting recognition with extraction of letter fragments
Wrobel M., Starczewski J.T., Napoli C., Handwriting recognition with extraction of letter fragments, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 183-192, 2017, Cites: 14
Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes
Kapuscinski T., Nowicki R.K., Napoli C., Comparison of effectiveness of multi-objective genetic algorithms in optimization of invertible S-boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 466-476, 2017, Cites: 11
Parallel levenberg-marquardt algorithm without error backpropagation
Bilski J., Wilamowski B.M., Parallel levenberg-marquardt algorithm without error backpropagation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 25-39, 2017, Cites: 11
Heuristic regression function estimation methods for data streams with concept drift
Jaworski M., Duda P., Rutkowski L., Najgebauer P., Pawlak M., Heuristic regression function estimation methods for data streams with concept drift, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 726-737, 2017, Cites: 10
The bag-of-words method with dictionary analysis by evolutionary algorithm
Gabryel M., Capizzi G., The bag-of-words method with dictionary analysis by evolutionary algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 43-51, 2017, Cites: 8
Interpretability of fuzzy systems designed in the process of evolutionary learning
Cpalka K., Interpretability of fuzzy systems designed in the process of evolutionary learning, Studies in Computational Intelligence, 684, 684, 91-130, 2017, Cites: 7
The concept on nonlinear modelling of dynamic objects based on state transition algorithm and genetic programming
Bartczuk L., Dziwinski P., Red'Ko V.G., The concept on nonlinear modelling of dynamic objects based on state transition algorithm and genetic programming, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 209-220, 2017, Cites: 6
Convolutional neural networks for time series classification
Zebik M., Korytkowski M., Angryk R., Scherer R., Convolutional neural networks for time series classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 635-642, 2017, Cites: 6
Detection of saliency map as image feature outliers using random projections based method
Damasevicius R., Maskeliunas R., Wozniak M., Polap D., Sidekerskiene T., Gabryel M., Detection of saliency map as image feature outliers using random projections based method, ICENCO 2017 - 13th International Computer Engineering Conference: Boundless Smart Societies, 2018-January, 2018-January, 85-90, 2017, Cites: 5
A method for non-linear modelling based on the capabilities of PSO and GA algorithms
Dziwinski P., Bartczuk L., Tingwen H., A method for non-linear modelling based on the capabilities of PSO and GA algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 221-232, 2017, Cites: 5
Environment recognition based on images using bag-of-words
Petraitis T., Maskeliunas R., Damasevicius R., Polap D., Wozniak M., Gabryel M., Environment recognition based on images using bag-of-words, IJCCI 2017 - Proceedings of the 9th International Joint Conference on Computational Intelligence, 166-176, 2017, Cites: 5
Hybrid initialization in the process of evolutionary learning
Lapa K., Cpalka K., Hayashi Y., Hybrid initialization in the process of evolutionary learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 380-393, 2017, Cites: 4
A method for genetic selection of the most characteristic descriptors of the dynamic signature
Zalasinski M., Cpalka K., Hayashi Y., A method for genetic selection of the most characteristic descriptors of the dynamic signature, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 747-760, 2017, Cites: 4
Stability evaluation of the dynamic signature partitions over time
Zalasinski M., Cpalka K., Er M.J., Stability evaluation of the dynamic signature partitions over time, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 733-746, 2017, Cites: 4
The bag-of-words methods with pareto-fronts for similar image retrieval
Gabryel M., The bag-of-words methods with pareto-fronts for similar image retrieval, Communications in Computer and Information Science, 756, 756, 374-384, 2017, Cites: 4
Some remarks about tracing digital cameras-faster method and usable countermeasure
Bernacki J., Klonowski M., Syga P., Some remarks about tracing digital cameras-faster method and usable countermeasure, ICETE 2017 - Proceedings of the 14th International Joint Conference on e-Business and Telecommunications, 4, 4, 343-350, 2017, Cites: 4
Parallel implementation of the givens rotations in the neural network learning algorithm
Bilski J., Kowalczyk B., Zurada J.M., Parallel implementation of the givens rotations in the neural network learning algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 14-24, 2017, Cites: 4
Fuzzy PID controllers with FIR filtering and a method for their construction
Lapa K., Cpalka K., Przybyl A., Saito T., Fuzzy PID controllers with FIR filtering and a method for their construction, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 292-307, 2017, Cites: 4
A method for nonlinear fuzzy modelling using population based algorithm with flexibly selectable operators
Lapa K., Cpalka K., Wang L., A method for nonlinear fuzzy modelling using population based algorithm with flexibly selectable operators, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 263-278, 2017, Cites: 3
Improvement of the validity index for determination of an appropriate data partitioning
Starczewski A., Krzyzak A., Improvement of the validity index for determination of an appropriate data partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 159-170, 2017, Cites: 3
Elastic FOPID+FIR controller design using hybrid population-based algorithm
Lapa K., Elastic FOPID+FIR controller design using hybrid population-based algorithm, Advances in Intelligent Systems and Computing, 522, 522, 15-26, 2017, Cites: 3
A method for changes prediction of the dynamic signature global features over time
Zalasinski M., Lapa K., Cpalka K., Saito T., A method for changes prediction of the dynamic signature global features over time, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 761-772, 2017, Cites: 3
Novel method for joining missing line fragments for medical image analysis
Najgebauer P., Rutkowski L., Scherer R., Novel method for joining missing line fragments for medical image analysis, 2017 22nd International Conference on Methods and Models in Automation and Robotics, MMAR 2017, 861-866, 2017, Cites: 3
Distributed image retrieval with color and keypoint features
Lagiewka M., Korytkowski M., Scherer R., Distributed image retrieval with color and keypoint features, Proceedings - 2017 IEEE International Conference on INnovations in Intelligent SysTems and Applications, INISTA 2017, 45-50, 2017, Cites: 3
Case study: Interpretability of fuzzy systems applied to nonlinear modelling and control
Cpalka K., Case study: Interpretability of fuzzy systems applied to nonlinear modelling and control, Studies in Computational Intelligence, 684, 684, 131-162, 2017, Cites: 2
Interest point localization based on edge detection according to gestalt laws
Najgebauer P., Rutkowski L., Scherer R., Interest point localization based on edge detection according to gestalt laws, 2017 2nd IEEE International Conference on Computational Intelligence and Applications, ICCIA 2017, 2017-January, 2017-January, 349-353, 2017, Cites: 2
Porous silica templated nanomaterials for artificial intelligence and IT technologies
Laskowska M., Laskowski L., Jelonkiewicz J., Piech H., Galkowski T., Boullanger A., Porous silica templated nanomaterials for artificial intelligence and IT technologies, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 509-517, 2017, Cites: 2
Local keypoint-based image detector with object detection
Grycuk R., Scherer M., Voloshynovskiy S., Local keypoint-based image detector with object detection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 507-517, 2017, Cites: 2
Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography
Cierniak R., Bilski J., Smolag J., Pluta P., Shah N., Parallel realizations of the iterative statistical reconstruction algorithm for 3D computed tomography, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 473-484, 2017, Cites: 1
A study of cluster validity indices for real-life data
Starczewski A., Krzyzak A., A study of cluster validity indices for real-life data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 148-158, 2017, Cites: 1
The novel method of the estimation of the fourier transform based on noisy measurements
Galkowski T., Pawlak M., The novel method of the estimation of the fourier transform based on noisy measurements, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 52-61, 2017, Cites: 1
A method for design of hardware emulators for a distributed network environment
Przybyl A., Er M.J., A method for design of hardware emulators for a distributed network environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, 318-336, 2017, Cites: 1
Improving fuzzy systems interpretability by appropriate selection of their structure
Cpalka K., Improving fuzzy systems interpretability by appropriate selection of their structure, Studies in Computational Intelligence, 684, 684, 37-60, 2017, Cites: 1
Introduction to fuzzy system interpretability
Cpalka K., Introduction to fuzzy system interpretability, Studies in Computational Intelligence, 684, 684, 27-36, 2017, Cites: 1
Case study: Interpretability of fuzzy systems applied to identity verification
Cpalka K., Case study: Interpretability of fuzzy systems applied to identity verification, Studies in Computational Intelligence, 684, 684, 163-189, 2017, Cites: 0
Concluding remarks and future perspectives
Cpalka K., Concluding remarks and future perspectives, Studies in Computational Intelligence, 684, 684, 191-193, 2017, Cites: 0
Selected topics in fuzzy systems designing
Cpalka K., Selected topics in fuzzy systems designing, Studies in Computational Intelligence, 684, 684, 11-25, 2017, Cites: 0
Introduction
Cpalka K., Introduction, Studies in Computational Intelligence, 684, 684, 1-10, 2017, Cites: 0
Weighted fuzzy genetic programming algorithm for structure and parameters selection of fuzzy systems for nonlinear modelling
Lapa K., Cpalka K., Weighted fuzzy genetic programming algorithm for structure and parameters selection of fuzzy systems for nonlinear modelling, Advances in Intelligent Systems and Computing, 521, 521, 157-174, 2017, Cites: 0
Narx neural network for prediction of refresh timeout in PIM–DM multicast routing
Vladymyrska N., Wrobel M., Starczewski J.T., Hnatushenko V., Narx neural network for prediction of refresh timeout in PIM–DM multicast routing, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, 199-205, 2017, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10245 LNAI, 10245 LNAI, v-vi, 2017, Cites: 0
A new algorithm for online management of fuzzy rules base for nonlinear modeling
Lapa K., A new algorithm for online management of fuzzy rules base for nonlinear modeling, Advances in Intelligent Systems and Computing, 521, 521, 15-28, 2017, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 10246 LNAI, 10246 LNAI, V-VI, 2017, Cites: 0
Interpretability of fuzzy systems designed in the process of gradient learning
Cpalka K., Interpretability of fuzzy systems designed in the process of gradient learning, Studies in Computational Intelligence, 684, 684, 61-90, 2017, Cites: 0
Environment Recognition based on Images using Bag-of-Words
Petraitis T., Maskeliunas R., Damasevicius R., Polap D., Wozniak M., Gabryel M., Environment Recognition based on Images using Bag-of-Words, International Joint Conference on Computational Intelligence, 1, 1, 166-176, 2017, Cites: 0

2016 (65)

Fast image classification by boosting fuzzy classifiers
Korytkowski M., Rutkowski L., Scherer R., Fast image classification by boosting fuzzy classifiers, Information Sciences, 327, 327, 175-182, 2016, Cites: 138
A new algorithm for identity verification based on the analysis of a handwritten dynamic signature
Cpalka K., Zalasinski M., Rutkowski L., A new algorithm for identity verification based on the analysis of a handwritten dynamic signature, Applied Soft Computing Journal, 43, 43, 47-56, 2016, Cites: 89
A new approach to nonlinear modelling of dynamic systems based on fuzzy rules
Bartczuk L., Przybyl A., Cpalka K., A new approach to nonlinear modelling of dynamic systems based on fuzzy rules, International Journal of Applied Mathematics and Computer Science, 26, 26, 603-621, 2016, Cites: 36
An idea of the dynamic signature verification based on a hybrid approach
Zalasinski M., Cpalka K., Rakus-Andersson E., An idea of the dynamic signature verification based on a hybrid approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 232-246, 2016, Cites: 28
New algorithm for on-line signature verification using characteristic hybrid partitions
Zalasinski M., Cpalka K., New algorithm for on-line signature verification using characteristic hybrid partitions, Advances in Intelligent Systems and Computing, 432, 432, 147-157, 2016, Cites: 27
Responsive web design: Testing usability of mobile web applications
Bernacki J., Blazejczyk I., Indyka-Piasecka A., Kopel M., Kukla E., Trawinski B., Responsive web design: Testing usability of mobile web applications, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9621, 9621, 257-269, 2016, Cites: 24
Preprocessing large data sets by the use of quick sort algorithm
Wozniak M., Marszalek Z., Gabryel M., Nowicki R.K., Preprocessing large data sets by the use of quick sort algorithm, Advances in Intelligent Systems and Computing, 364, 364, 111-121, 2016, Cites: 23
Gene expression programming in correction modelling of nonlinear dynamic objects
Bartczuk L., Gene expression programming in correction modelling of nonlinear dynamic objects, Advances in Intelligent Systems and Computing, 429, 429, 125-134, 2016, Cites: 19
A new approach to the dynamic signature verification aimed at minimizing the number of global features
Zalasinski M., Cpalka K., Hayashi Y., A new approach to the dynamic signature verification aimed at minimizing the number of global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 218-231, 2016, Cites: 18
A method for automatic adjustment of ensemble size in stream data mining
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., A method for automatic adjustment of ensemble size in stream data mining, Proceedings of the International Joint Conference on Neural Networks, 2016-October, 2016-October, 9-15, 2016, Cites: 17
Content-based image retrieval optimization by differential evolution
Grycuk R., Gabryel M., Nowicki R., Scherer R., Content-based image retrieval optimization by differential evolution, 2016 IEEE Congress on Evolutionary Computation, CEC 2016, 86-93, 2016, Cites: 17
A bag-of-features algorithm for applications using a NoSQL database
Gabryel M., A bag-of-features algorithm for applications using a NoSQL database, Communications in Computer and Information Science, 639, 639, 332-343, 2016, Cites: 17
An application of firefly algorithm to position traffic in NoSQL database systems
Wozniak M., Gabryel M., Nowicki R.K., Nowak B.A., An application of firefly algorithm to position traffic in NoSQL database systems, Advances in Intelligent Systems and Computing, 416, 416, 259-272, 2016, Cites: 16
On the application of a hybrid genetic-firework algorithm for controllers structure and parameters selection
Lapa K., Cpalka K., On the application of a hybrid genetic-firework algorithm for controllers structure and parameters selection, Advances in Intelligent Systems and Computing, 429, 429, 111-123, 2016, Cites: 16
A new method of the intelligent modeling of the nonlinear dynamic objects with fuzzy detection of the operating points
Dziwinski P., Avedyan E.D., A new method of the intelligent modeling of the nonlinear dynamic objects with fuzzy detection of the operating points, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 293-305, 2016, Cites: 15
Application of genetic algorithms in the construction of invertible substitution boxes
Kapuscinski T., Nowicki R.K., Napoli C., Application of genetic algorithms in the construction of invertible substitution boxes, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 380-391, 2016, Cites: 14
The bag-of-features algorithm for practical applications using the MySQL database
Gabryel M., The bag-of-features algorithm for practical applications using the MySQL database, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 635-646, 2016, Cites: 14
New algorithm for on-line signature verification using characteristic global features
Zalasinski M., New algorithm for on-line signature verification using characteristic global features, Advances in Intelligent Systems and Computing, 432, 432, 137-146, 2016, Cites: 14
Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples
Nowicki R.K., Nowak B.A., Wozniak M., Application of rough sets in k nearest neighbours algorithm for classification of incomplete samples, Advances in Intelligent Systems and Computing, 416, 416, 243-257, 2016, Cites: 13
A modification of the Silhouette index for the improvement of cluster validity assessment
Starczewski A., Krzyzak A., A modification of the Silhouette index for the improvement of cluster validity assessment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 114-124, 2016, Cites: 13
Application of the givens rotations in the neural network learning algorithm
Bilski J., Kowalczyk B., Zurada J.M., Application of the givens rotations in the neural network learning algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 46-56, 2016, Cites: 13
A new method for generating of fuzzy rules for the nonlinear modelling based on semantic genetic programming
Bartczuk L., Lapa K., Koprinkova-Hristova P., A new method for generating of fuzzy rules for the nonlinear modelling based on semantic genetic programming, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 262-278, 2016, Cites: 12
Parallel learning of feedforward neural networks without error backpropagation
Bilski J., Wilamowski B.M., Parallel learning of feedforward neural networks without error backpropagation, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 57-69, 2016, Cites: 12
Self organizing maps for 3D face understanding
Starczewski J.T., Pabiasz S., Vladymyrska N., Marvuglia A., Napoli C., Wozniak M., Self organizing maps for 3D face understanding, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 210-217, 2016, Cites: 11
The method of hardware implementation of fuzzy systems on FPGA
Przybyl A., Joo Er M., The method of hardware implementation of fuzzy systems on FPGA, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 284-298, 2016, Cites: 9
Image descriptor based on edge detection and crawler algorithm
Grycuk R., Gabryel M., Scherer M., Voloshynovskiy S., Image descriptor based on edge detection and crawler algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 647-659, 2016, Cites: 9
Estimating CPU features by browser fingerprinting
Saito T., Yasuda K., Ishikawa T., Hosoi R., Takahashi K., Chen Y., Zalasinski M., Estimating CPU features by browser fingerprinting, Proceedings - 2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2016, 587-592, 2016, Cites: 8
Usability testing of a mobile friendly web conference service
Blazejczyk I., Trawinski B., Indyka-Piasecka A., Kopel M., Kukla E., Bernacki J., Usability testing of a mobile friendly web conference service, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9875 LNCS, 9875 LNCS, 565-579, 2016, Cites: 8
Comparison of algebraic and analytical approaches to the formulation of the statistical model-based reconstruction problem for X-ray computed tomography
Cierniak R., Lorent A., Comparison of algebraic and analytical approaches to the formulation of the statistical model-based reconstruction problem for X-ray computed tomography, Computerized Medical Imaging and Graphics, 52, 52, 19-27, 2016, Cites: 8
A new approach for using the fuzzy decision trees for the detection of the significant operating points in the nonlinear modeling
Dziwinski P., Avedyan E.D., A new approach for using the fuzzy decision trees for the detection of the significant operating points in the nonlinear modeling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 279-292, 2016, Cites: 6
Nonparametric estimation of edge values of regression functions
Galkowski T., Pawlak M., Nonparametric estimation of edge values of regression functions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 49-59, 2016, Cites: 6
Iron Doped SBA-15 Mesoporous Silica Studied by Mössbauer Spectroscopy
Laskowski ., Laskowska M., Jelonkiewicz J., Galkowski T., Pawlik P., Piech H., Doskocz M., Iron Doped SBA-15 Mesoporous Silica Studied by Mössbauer Spectroscopy, Journal of Nanomaterials, 2016, 2016, 2016, Cites: 6
Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking
Kempa W.M., Wozniak M., Nowicki R.K., Gabryel M., Damasevicius R., Transient solution for queueing delay distribution in the GI/M/1/K-type mode with “queued” waking up and balking, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 340-351, 2016, Cites: 6
Hybrid splitting criterion in decision trees for data stream mining
Jaworski M., Rutkowski L., Pawlak M., Hybrid splitting criterion in decision trees for data stream mining, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 60-72, 2016, Cites: 6
Aspects of evolutionary construction of new flexible PID-fuzzy controller
Lapa K., Szczypta J., Saito T., Aspects of evolutionary construction of new flexible PID-fuzzy controller, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 450-464, 2016, Cites: 6
Adaptation of deep belief networks to modern multicore architectures
Olas T., Mleczko W.K., Nowicki R.K., Wyrzykowski R., Adaptation of deep belief networks to modern multicore architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9573, 9573, 459-472, 2016, Cites: 5
New method for fuzzy nonlinear modelling based on genetic programming
Lapa K., Cpalka K., Koprinkova-Hristova P., New method for fuzzy nonlinear modelling based on genetic programming, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 432-449, 2016, Cites: 5
A new method for generating nonlinear correction models of dynamic objects based on semantic genetic programming
Bartczuk L., Galushkin A.I., A new method for generating nonlinear correction models of dynamic objects based on semantic genetic programming, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 249-261, 2016, Cites: 5
Novel rough neural network for classification with missing data
Nowicki R.K., Scherer R., Rutkowski L., Novel rough neural network for classification with missing data, 2016 21st International Conference on Methods and Models in Automation and Robotics, MMAR 2016, 820-825, 2016, Cites: 5
Method of evolutionary designing of FPGA-based controllers
Przybyl A., Szczypta J., Method of evolutionary designing of FPGA-based controllers, Przeglad Elektrotechniczny, 92, 92, 174-179, 2016, Cites: 5
A new approach to designing of intelligent emulators working in a distributed environment
Przybyl A., Er M.J., A new approach to designing of intelligent emulators working in a distributed environment, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 546-558, 2016, Cites: 4
Nonlinear pattern classification using fuzzy system and hybrid genetic-imperialist algorithm
Lapa K., Cpalka K., Nonlinear pattern classification using fuzzy system and hybrid genetic-imperialist algorithm, Advances in Intelligent Systems and Computing, 432, 432, 159-171, 2016, Cites: 4
The concept of molecular neurons
Laskowski L., Laskowska M., Piech H., Galkowski T., Boullanger A., The concept of molecular neurons, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 494-501, 2016, Cites: 4
Query-by-example image retrieval in Microsoft SQL server
Staszewski P., Woldan P., Korytkowski M., Scherer R., Wang L., Query-by-example image retrieval in Microsoft SQL server, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 746-754, 2016, Cites: 4
A new proposition of the activation function for significant improvement of neural networks performance
Bilski J., Galushkin A.I., A new proposition of the activation function for significant improvement of neural networks performance, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 35-45, 2016, Cites: 3
Predicting success of bank direct marketing by neuro-fuzzy systems
Scherer M., Smolag J., Gaweda A., Predicting success of bank direct marketing by neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 570-576, 2016, Cites: 3
The method of the evolutionary designing the elastic controller structure
Przybyl A., Lapa K., Szczypta J., Wang L., The method of the evolutionary designing the elastic controller structure, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 476-492, 2016, Cites: 3
New approach for interpretability of neuro-fuzzy systems with parametrized triangular norms
Lapa K., Cpalka K., Wang L., New approach for interpretability of neuro-fuzzy systems with parametrized triangular norms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 248-265, 2016, Cites: 3
Fast computing framework for convolutional neural networks
Korytkowski M., Staszewski P., Woldan P., Scherer R., Fast computing framework for convolutional neural networks, Proceedings - 2016 IEEE International Conferences on Big Data and Cloud Computing, BDCloud 2016, Social Computing and Networking, SocialCom 2016 and Sustainable Computing and Communications, SustainCom 2016, 118-123, 2016, Cites: 2
On the Cesàro-means-based orthogonal series approach to learning time-varying regression functions
Duda P., Pietruczuk L., Jaworski M., Krzyzak A., On the Cesàro-means-based orthogonal series approach to learning time-varying regression functions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 37-48, 2016, Cites: 2
Neural video compression based on surf scene change detection algorithm
Grycuk R., Knop M., Neural video compression based on surf scene change detection algorithm, Advances in Intelligent Systems and Computing, 389, 389, 105-112, 2016, Cites: 2
Rough restricted Boltzmann machine -New architecture for incomplete input data
Mleczko W.K., Nowicki R.K., Angryk R., Rough restricted Boltzmann machine -New architecture for incomplete input data, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 114-125, 2016, Cites: 2
Color-based large-scale image retrieval with limited hardware resources
Lagiewka M., Scherer R., Angryk R., Color-based large-scale image retrieval with limited hardware resources, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 689-699, 2016, Cites: 2
A novel convolutional neural network with glial cells
Korytkowski M., A novel convolutional neural network with glial cells, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 670-679, 2016, Cites: 2
Novel image descriptor based on color spatial distribution
Najgebauer P., Korytkowski M., Barranco C.D., Scherer R., Novel image descriptor based on color spatial distribution, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 712-722, 2016, Cites: 2
RFID security: A method for tracking prevention
Bernacki J., Kolaczek G., RFID security: A method for tracking prevention, Communications in Computer and Information Science, 659, 659, 241-249, 2016, Cites: 1
On the application of orthogonal series density estimation for image classification based on feature description
Duda P., Jaworski M., Pietruczuk L., Korytkowski M., Gabryel M., Scherer R., On the application of orthogonal series density estimation for image classification based on feature description, Advances in Intelligent Systems and Computing, 364, 364, 529-540, 2016, Cites: 1
New approach for nonlinear modelling based on online designing of the fuzzy rule base
Lapa K., Cpalka K., Hayashi Y., New approach for nonlinear modelling based on online designing of the fuzzy rule base, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 230-247, 2016, Cites: 1
Artificial intelligence and soft computing: 15th international conference, ICAISC 2016 Zakopane, Poland, June 12-16, 2016 proceedings, Part I
Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L.A., Zurada J.M., Artificial intelligence and soft computing: 15th international conference, ICAISC 2016 Zakopane, Poland, June 12-16, 2016 proceedings, Part I, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, 2016, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9692, 9692, V-VI, 2016, Cites: 0
Analytical statistical approach for fan-beam scanners
Cierniak R., Analytical statistical approach for fan-beam scanners, Advances in Intelligent Systems and Computing, 471, 471, 231-243, 2016, Cites: 0
Regularization methods for the analytical statistical reconstruction problem in medical computed tomography
Cierniak R., Lorent A., Pluta P., Shah N., Regularization methods for the analytical statistical reconstruction problem in medical computed tomography, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, 147-158, 2016, Cites: 0
Aspects of structure selection and parameters tuning of control systems using hybrid genetic-fruit fly algorithm
Szczypta J., Lapa K., Aspects of structure selection and parameters tuning of control systems using hybrid genetic-fruit fly algorithm, Advances in Intelligent Systems and Computing, 429, 429, 101-110, 2016, Cites: 0
Fast image search by trees of keypoint descriptors
Najgebauer P., Scherer R., Fast image search by trees of keypoint descriptors, Advances in Intelligent Systems and Computing, 364, 364, 541-552, 2016, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9693, 9693, V-VI, 2016, Cites: 0

2015 (42)

A new method for data stream mining based on the misclassification error
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., A new method for data stream mining based on the misclassification error, IEEE Transactions on Neural Networks and Learning Systems, 26, 26, 1048-1059, 2015, Cites: 97
Performance evaluation of the silhouette index
Starczewski A., Krzyzak A., Performance evaluation of the silhouette index, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 49-58, 2015, Cites: 67
A new approach to design of control systems using genetic programming
Cpalka K., Lapa K., Przybyl A., A new approach to design of control systems using genetic programming, Information Technology and Control, 44, 44, 433-442, 2015, Cites: 40
Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks
Bilski J., Smolag J., Parallel Architectures for Learning the RTRN and Elman Dynamic Neural Networks, IEEE Transactions on Parallel and Distributed Systems, 26, 26, 2561-2570, 2015, Cites: 39
Can we process 2D images using artificial bee colony?
Wozniak M., Polap D., Gabryel M., Nowicki R.K., Napoli C., Tramontana E., Can we process 2D images using artificial bee colony?, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 660-671, 2015, Cites: 36
Novel approach toward medical signals classifier
Wozniak M., Polap D., Nowicki R.K., Napoli C., Pappalardo G., Tramontana E., Novel approach toward medical signals classifier, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 36
A multiscale image compressor with RBFNN and Discrete Wavelet decomposition
Wozniak M., Napoli C., Tramontana E., Capizzi G., Lo Sciuto G., Nowicki R.K., Starczewski J.T., A multiscale image compressor with RBFNN and Discrete Wavelet decomposition, Proceedings of the International Joint Conference on Neural Networks, 2015-September, 2015-September, 2015, Cites: 36
Toward work groups classification based on probabilistic neural network approach
Napoli C., Pappalardo G., Tramontana E., Nowicki R.K., Starczewski J.T., Wozniak M., Toward work groups classification based on probabilistic neural network approach, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 79-89, 2015, Cites: 36
Multi-class nearest neighbour classifier for incomplete data handling
Nowak B.A., Nowicki R.K., Wozniak M., Napoli C., Multi-class nearest neighbour classifier for incomplete data handling, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 469-480, 2015, Cites: 36
New fast algorithm for the dynamic signature verification using global features values
Zalasinski M., Cpalka K., Hayashi Y., New fast algorithm for the dynamic signature verification using global features values, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 175-188, 2015, Cites: 33
Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks
Bilski J., Smolag J., Zurada J.M., Parallel approach to the Levenberg-marquardt learning algorithm for feedforward neural networks, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 3-14, 2015, Cites: 22
Aspects of structure and parameters selection of control systems using selected multi-population algorithms
Lapa K., Szczypta J., Venkatesan R., Aspects of structure and parameters selection of control systems using selected multi-population algorithms, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 247-260, 2015, Cites: 20
Multi-layer architecture for storing visual data based on WCF and microsoft SQL server database
Grycuk R., Gabryel M., Scherer R., Voloshynovskiy S., Multi-layer architecture for storing visual data based on WCF and microsoft SQL server database, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 715-726, 2015, Cites: 19
An application of differential evolution to positioning queueing systems
Gabryel M., Wozniak M., Damasevicius R., An application of differential evolution to positioning queueing systems, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 379-390, 2015, Cites: 19
A new approach to nonlinear modeling based on significant operating points detection
Dziwinski P., Avedyan E.D., A new approach to nonlinear modeling based on significant operating points detection, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 364-378, 2015, Cites: 18
Rough deep belief network - application to incomplete handwritten digits pattern classification
Mleczko W.K., Kapuscinski T., Nowicki R.K., Rough deep belief network - application to incomplete handwritten digits pattern classification, Communications in Computer and Information Science, 538, 538, 400-411, 2015, Cites: 17
Image indexing and retrieval using GSOM algorithm
Gabryel M., Grycuk R., Korytkowski M., Holotyak T., Image indexing and retrieval using GSOM algorithm, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 706-714, 2015, Cites: 17
A new method for the dynamic signature verification based on the stable partitions of the signature
Zalasinski M., Cpalka K., Er M.J., A new method for the dynamic signature verification based on the stable partitions of the signature, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 161-174, 2015, Cites: 16
A new interpretability criteria for neuro-fuzzy systems for nonlinear classification
Lapa K., Cpalka K., Galushkin A.I., A new interpretability criteria for neuro-fuzzy systems for nonlinear classification, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 448-468, 2015, Cites: 11
Video key frame detection based on SURF algorithm
Grycuk R., Knop M., Mandal S., Video key frame detection based on SURF algorithm, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 566-576, 2015, Cites: 10
Bag-of-features image indexing and classification in microsoft SQL server relational database
Korytkowski M., Scherer R., Staszewski P., Woldan P., Bag-of-features image indexing and classification in microsoft SQL server relational database, Proceedings - 2015 IEEE 2nd International Conference on Cybernetics, CYBCONF 2015, 478-482, 2015, Cites: 9
New method for non-linear correction modelling of dynamic objects with genetic programming
Bartczuk L., Przybyl A., Koprinkova-Hristova P., New method for non-linear correction modelling of dynamic objects with genetic programming, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 318-329, 2015, Cites: 9