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 (496)

Last Sync Date: 2024-03-03

2024 (7)

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
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
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: 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
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
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: 0
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: 0

2023 (51)

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: 14
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: 11
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: 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
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: 4
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, 2023, Cites: 3
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: 3
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: 3
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
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: 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
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
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
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: 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
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: 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
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
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
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
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
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: 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
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
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
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
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
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
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
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: 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
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
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, 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
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
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
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 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
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
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 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, 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 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
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
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
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 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
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
A New Linguistic Fuzzy PRISM Algorithm
Bartczuk L., A New Linguistic Fuzzy PRISM Algorithm, IEEE International Conference on Fuzzy Systems, 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

2022 (32)

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: 39
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: 31
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: 27
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: 25
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: 16
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: 15
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-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: 10
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
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
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
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: 7
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: 7
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: 6
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
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: 5
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
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: 3
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 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: 2
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
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
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
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: 1
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
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
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: 0
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
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: 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
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
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

2021 (32)

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: 105
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: 79
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: 39
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: 35
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
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
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
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
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: 9
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: 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
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
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
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
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
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
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
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: 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
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
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
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
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
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
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
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
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

2020 (64)

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: 91
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: 80
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: 66
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: 65
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: 61
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: 58
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: 36
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: 30
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: 28
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
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: 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: 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: 18
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
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: 15
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: 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: 11
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
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
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: 10
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: 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
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
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: 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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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: 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
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
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
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
Hybrid Splitting Criteria
Rutkowski L., Jaworski M., Duda P., Hybrid Splitting Criteria, Studies in Big Data, 56, 56, 91-113, 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
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
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
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
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
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
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
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
Classification
Rutkowski L., Jaworski M., Duda P., Classification, Studies in Big Data, 56, 56, 287-308, 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
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
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
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
Regression
Rutkowski L., Jaworski M., Duda P., Regression, Studies in Big Data, 56, 56, 309-322, 2020, Cites: 0

2019 (29)

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: 12
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: 12
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
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
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
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
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: 3
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
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
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
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
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
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
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: 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
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
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
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
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
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
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
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
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
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

2018 (34)

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: 82
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: 45
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: 24
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
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
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: 16
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
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: 12
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: 11
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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

2017 (30)

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: 60
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: 46
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: 22
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
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 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
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
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
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
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 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
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
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
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
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
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: 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
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
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
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
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

2016 (44)

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: 137
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
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: 18
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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

2015 (27)

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: 63
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
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
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
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
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
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
SOM vs FCM vs PCA in 3D face recognition
Pabiasz S., Starczewski J.T., Marvuglia A., SOM vs FCM vs PCA in 3D face recognition, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 120-129, 2015, Cites: 6
The comparison of creating homogeneous and heterogeneous collaborative learning groups in intelligent tutoring systems
Bernacki J., Kozierkiewicz-HetmaNska A., The comparison of creating homogeneous and heterogeneous collaborative learning groups in intelligent tutoring systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9011, 9011, 46-55, 2015, Cites: 5
Neural Video Compression Algorithm
Knop M., Dobosz P., Neural Video Compression Algorithm, Advances in Intelligent Systems and Computing, 313 AISC, 313 AISC, 59-66, 2015, Cites: 5
Improvement of the multiple-view learning based on the self-organizing maps
Galkowski T., Starczewski A., Fu X., Improvement of the multiple-view learning based on the self-organizing maps, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 3-12, 2015, Cites: 4
Orthogonal series estimation of regression functions in nonstationary conditions
Galkowski T., Pawlak M., Orthogonal series estimation of regression functions in nonstationary conditions, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 427-435, 2015, Cites: 3
Fast dictionary matching for content-based image retrieval
Najgebauer P., Rygal J., Nowak T., Romanowski J., Rutkowski L., Voloshynovskiy S., Scherer R., Fast dictionary matching for content-based image retrieval, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, 747-756, 2015, Cites: 2
Customization of joint articulations using soft computing methods
Szarek A., Korytkowski M., Rutkowski L., Scherer M., Szyprowski J., Kostadinov D., Customization of joint articulations using soft computing methods, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, 151-160, 2015, Cites: 1
A conception for use of user profile to prediction learning effects in Intelligent Tutoring Systems
Kozierkiewicz-Hetmanska A., Bernacki J., A conception for use of user profile to prediction learning effects in Intelligent Tutoring Systems, Proceedings - 2015 IEEE 2nd International Conference on Cybernetics, CYBCONF 2015, 97-101, 2015, Cites: 1
Modeling Learning Group's Communication in Intelligent Tutoring Systems
Kozierkiewicz-Hetmanska A., Bernacki J., Modeling Learning Group's Communication in Intelligent Tutoring Systems, Proceedings - 2nd European Network Intelligence Conference, ENIC 2015, 140-144, 2015, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9119, 9119, V-VII, 2015, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 9120, 9120, V-VII, 2015, Cites: 0

2014 (30)

The CART decision tree for mining data streams
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., The CART decision tree for mining data streams, Information Sciences, 266, 266, 1-15, 2014, Cites: 250
Decision trees for mining data streams based on the gaussian approximation
Rutkowski L., Jaworski M., Pietruczuk L., Duda P., Decision trees for mining data streams based on the gaussian approximation, IEEE Transactions on Knowledge and Data Engineering, 26, 26, 108-119, 2014, Cites: 139
On-line signature verification using vertical signature partitioning
Cpalka K., Zalasinski M., On-line signature verification using vertical signature partitioning, Expert Systems with Applications, 41, 41, 4170-4180, 2014, Cites: 86
A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects
Cpalka K., Lapa K., Przybyl A., Zalasinski M., A new method for designing neuro-fuzzy systems for nonlinear modelling with interpretability aspects, Neurocomputing, 135, 135, 203-217, 2014, Cites: 81
New method for the on-line signature verification based on horizontal partitioning
Cpalka K., Zalasinski M., Rutkowski L., New method for the on-line signature verification based on horizontal partitioning, Pattern Recognition, 47, 47, 2652-2661, 2014, Cites: 81
New method for design of fuzzy systems for nonlinear modelling using different criteria of interpretability
Lapa K., Cpalka K., Wang L., New method for design of fuzzy systems for nonlinear modelling using different criteria of interpretability, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 217-232, 2014, Cites: 39
Centroid of triangular and Gaussian type-2 fuzzy sets
Starczewski J.T., Centroid of triangular and Gaussian type-2 fuzzy sets, Information Sciences, 280, 280, 289-306, 2014, Cites: 36
New method for dynamic signature verification based on global features
Zalasinski M., Cpalka K., Hayashi Y., New method for dynamic signature verification based on global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 231-245, 2014, Cites: 35
New method for dynamic signature verification using hybrid partitioning
Zalasinski M., Cpalka K., Er M.J., New method for dynamic signature verification using hybrid partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 216-230, 2014, Cites: 33
A new algorithm for identification of significant operating points using swarm intelligence
Dziwinski P., Bartczuk L., Przybyl A., Avedyan E.D., A new algorithm for identification of significant operating points using swarm intelligence, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 349-362, 2014, Cites: 32
From single image to list of objects based on edge and blob detection
Grycuk R., Gabryel M., Korytkowski M., Scherer R., Voloshynovskiy S., From single image to list of objects based on edge and blob detection, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 605-615, 2014, Cites: 32
The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks
Bilski J., Smolag J., Galushkin A.I., The parallel approach to the conjugate gradient learning algorithm for the feedforward neural networks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 12-21, 2014, Cites: 26
New method for nonlinear fuzzy correction modelling of dynamic objects
Bartczuk L., Przybyl A., Koprinkova-Hristova P., New method for nonlinear fuzzy correction modelling of dynamic objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 169-180, 2014, Cites: 26
Content-Based Image Indexing by Data Clustering and Inverse Document Frequency
Grycuk R., Gabryel M., Korytkowski M., Scherer R., Content-Based Image Indexing by Data Clustering and Inverse Document Frequency, Communications in Computer and Information Science, 424, 424, 374-383, 2014, Cites: 26
Aspects of the selection of the structure and parameters of controllers using selected population based algorithms
Szczypta J., Lapa K., Shao Z., Aspects of the selection of the structure and parameters of controllers using selected population based algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 440-454, 2014, Cites: 17
A novel application of Hoeffding's inequality to decision trees construction for data streams
Duda P., Jaworski M., Pietruczuk L., Rutkowski L., A novel application of Hoeffding's inequality to decision trees construction for data streams, Proceedings of the International Joint Conference on Neural Networks, 3324-3330, 2014, Cites: 15
Improved digital image segmentation based on stereo vision and mean shift algorithm
Grycuk R., Gabryel M., Korytkowski M., Romanowski J., Scherer R., Improved digital image segmentation based on stereo vision and mean shift algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8384 LNCS, 8384 LNCS, 433-443, 2014, Cites: 13
The Parzen kernel approach to learning in non-stationary environment
Pietruczuk L., Rutkowski L., Jaworski M., Duda P., The Parzen kernel approach to learning in non-stationary environment, Proceedings of the International Joint Conference on Neural Networks, 3319-3323, 2014, Cites: 11
The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets
Nowak B.A., Nowicki R.K., Starczewski J.T., Marvuglia A., The learning of neuro-fuzzy classifier with fuzzy rough sets for imprecise datasets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 256-266, 2014, Cites: 10
The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features
Nowicki R.K., Nowak B.A., Starczewski J.T., Cpalka K., The learning of neuro-fuzzy approximator with fuzzy rough sets in case of missing features, Proceedings of the International Joint Conference on Neural Networks, 3759-3766, 2014, Cites: 10
Nonparametric function fitting in the presence of nonstationary noise
Galkowski T., Pawlak M., Nonparametric function fitting in the presence of nonstationary noise, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 531-538, 2014, Cites: 9
Genetic fuzzy classifier with fuzzy rough sets for imprecise data
Starczewski J.T., Nowicki R.K., Nowak B.A., Genetic fuzzy classifier with fuzzy rough sets for imprecise data, IEEE International Conference on Fuzzy Systems, 1382-1389, 2014, Cites: 8
A new three-dimensional facial landmarks in recognition
Pabiasz S., Starczewski J.T., Marvuglia A., A new three-dimensional facial landmarks in recognition, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 179-186, 2014, Cites: 7
Nonparametric extension of regression functions outside domain
Galkowski T., Pawlak M., Nonparametric extension of regression functions outside domain, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 518-530, 2014, Cites: 6
Content-based image retrieval by dictionary of local feature descriptors
Najgebauer P., Nowak T., Romanowski J., Gabryel M., Korytkowski M., Scherer R., Content-based image retrieval by dictionary of local feature descriptors, Proceedings of the International Joint Conference on Neural Networks, 512-517, 2014, Cites: 5
Creating collaborative learning groups in intelligent tutoring systems
Bernacki J., Kozierkiewicz-Hetmanska A., Creating collaborative learning groups in intelligent tutoring systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8671, 8671, 184-193, 2014, Cites: 5
Spatial keypoint representation for visual object retrieval
Nowak T., Najgebauer P., Romanowski J., Gabryel M., Korytkowski M., Scherer R., Kostadinov D., Spatial keypoint representation for visual object retrieval, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8468 LNAI, 8468 LNAI, 639-650, 2014, Cites: 4
A new image reconstruction from projections algorithm
Lorent A., Cierniak R., Dobosz P., Rebrova O., A new image reconstruction from projections algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 725-732, 2014, Cites: 1
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
Rutkowski L., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8467 LNAI, 8467 LNAI, 2014, Cites: 1
Using of EM algorithm to image reconstruction problem with tomography noises
Dobosz P., Cierniak R., Using of EM algorithm to image reconstruction problem with tomography noises, Advances in Intelligent Systems and Computing, 233, 233, 37-43, 2014, Cites: 0

2013 (19)

Decision trees for mining data streams based on the mcdiarmid's bound
Rutkowski L., Pietruczuk L., Duda P., Jaworski M., Decision trees for mining data streams based on the mcdiarmid's bound, IEEE Transactions on Knowledge and Data Engineering, 25, 25, 1272-1279, 2013, Cites: 162
On design of flexible neuro-fuzzy systems for nonlinear modelling
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On design of flexible neuro-fuzzy systems for nonlinear modelling, International Journal of General Systems, 42, 42, 706-720, 2013, Cites: 66
A new approach to designing interpretable models of dynamic systems
Lapa K., Przybyl A., Cpalka K., A new approach to designing interpretable models of dynamic systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 523-534, 2013, Cites: 45
Novel algorithm for the on-line signature verification using selected discretization points groups
Zalasinski M., Cpalka K., Novel algorithm for the on-line signature verification using selected discretization points groups, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 493-502, 2013, Cites: 39
New approach for the on-line signature verification based on method of horizontal partitioning
Zalasinski M., Cpalka K., New approach for the on-line signature verification based on method of horizontal partitioning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 342-350, 2013, Cites: 38
New algorithm for evolutionary selection of the dynamic signature global features
Zalasinski M., Lapa K., Cpalka K., New algorithm for evolutionary selection of the dynamic signature global features, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 113-121, 2013, Cites: 37
A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling
Lapa K., Zalasinski M., Cpalka K., A new method for designing and complexity reduction of neuro-fuzzy systems for nonlinear modelling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 329-344, 2013, Cites: 37
Parallel approach to learning of the recurrent Jordan neural network
Bilski J., Smolag J., Parallel approach to learning of the recurrent Jordan neural network, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 32-40, 2013, Cites: 26
Object detection by simple fuzzy classifiers generated by boosting
Gabryel M., Korytkowski M., Scherer R., Rutkowski L., Object detection by simple fuzzy classifiers generated by boosting, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 540-547, 2013, Cites: 24
Hybrid state variables - Fuzzy logic modelling of nonlinear objects
Bartczuk L., Przybyl A., Dziwinski P., Hybrid state variables - Fuzzy logic modelling of nonlinear objects, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 227-234, 2013, Cites: 19
Advanced concepts in fuzzy logic and systems with membership uncertainty
Starczewski J.T., Advanced concepts in fuzzy logic and systems with membership uncertainty, Studies in Fuzziness and Soft Computing, 284, 284, 1-319, 2013, Cites: 17
Kernel estimation of regression functions in the boundary regions
Galkowski T., Kernel estimation of regression functions in the boundary regions, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 158-166, 2013, Cites: 15
A new approach to determine three-dimensional facial landmarks
Pabiasz S., Starczewski J.T., A new approach to determine three-dimensional facial landmarks, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 286-296, 2013, Cites: 7
Representation of edge detection results based on graph theory
Najgebauer P., Nowak T., Romanowski J., Rygal J., Korytkowski M., Representation of edge detection results based on graph theory, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 588-601, 2013, Cites: 4
A clustering method based on the modified RS validity index
Starczewski A., A clustering method based on the modified RS validity index, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 242-250, 2013, Cites: 3
Extraction of objects from images using density of edges as basis for GrabCut algorithm
Rygal J., Najgebauer P., Romanowski J., Scherer R., Extraction of objects from images using density of edges as basis for GrabCut algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 613-623, 2013, Cites: 3
A novel graph-based descriptor for object matching
Nowak T., Najgebauer P., Rygal J., Scherer R., A novel graph-based descriptor for object matching, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 602-612, 2013, Cites: 2
Improved X-ray edge detection based on background extraction algorithm
Romanowski J., Nowak T., Najgebauer P., Litwinski S., Improved X-ray edge detection based on background extraction algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7895 LNAI, 7895 LNAI, 309-319, 2013, Cites: 1
Neuronal model-based image reconstruction from projections method
Lorent A., Knas M., Dobosz P., Neuronal model-based image reconstruction from projections method, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7894 LNAI, 7894 LNAI, 580-587, 2013, Cites: 0

2012 (17)

Novel online speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation
Rutkowski L., Przybyl A., Cpalka K., Novel online speed profile generation for industrial machine tool based on flexible neuro-fuzzy approximation, IEEE Transactions on Industrial Electronics, 59, 59, 1238-1247, 2012, Cites: 90
Novel algorithm for the on-line signature verification
Zalasinski M., Cpalka K., Novel algorithm for the on-line signature verification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 362-367, 2012, Cites: 45
Fully controllable ant colony system for text data clustering
Dziwinski P., Bartczuk L., Starczewski J.T., Fully controllable ant colony system for text data clustering, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7269 LNCS, 7269 LNCS, 199-205, 2012, Cites: 26
A new method for dealing with unbalanced linguistic term set
Bartczuk L., Dziwinski P., Starczewski J.T., A new method for dealing with unbalanced linguistic term set, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 207-212, 2012, Cites: 26
Parallel realisation of the recurrent multi layer perceptron learning
Bilski J., Smolag J., Parallel realisation of the recurrent multi layer perceptron learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 12-20, 2012, Cites: 24
Application of neural networks in assessing changes around implant after total hip arthroplasty
Szarek A., Korytkowski M., Rutkowski L., Scherer R., Szyprowski J., Application of neural networks in assessing changes around implant after total hip arthroplasty, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 335-340, 2012, Cites: 23
Forecasting wear of head and acetabulum in hip joint implant
Szarek A., Korytkowski M., Rutkowski L., Scherer R., Szyprowski J., Forecasting wear of head and acetabulum in hip joint implant, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 341-346, 2012, Cites: 14
Meshes vs. depth maps in face recognition systems
Pabiasz S., Starczewski J.T., Meshes vs. depth maps in face recognition systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 567-573, 2012, Cites: 5
Novel method for parasite detection in microscopic samples
Najgebauer P., Nowak T., Romanowski J., Rygal J., Korytkowski M., Scherer R., Novel method for parasite detection in microscopic samples, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 551-558, 2012, Cites: 4
Neuro-fuzzy systems
Rutkowski L., Cpalka K., Nowicki R., Pokropinska A., Scherer R., Neuro-fuzzy systems, Computational Complexity: Theory, Techniques, and Applications, 9781461418009, 9781461418009, 2069-2081, 2012, Cites: 4
Properties and structure of fast text search engine in context of semantic image analysis
Rygal J., Najgebauer P., Nowak T., Romanowski J., Gabryel M., Scherer R., Properties and structure of fast text search engine in context of semantic image analysis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 592-599, 2012, Cites: 4
A new hierarchical clustering algorithm
Starczewski A., A new hierarchical clustering algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 175-180, 2012, Cites: 3
A cluster validity index for hard clustering
Starczewski A., A cluster validity index for hard clustering, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 168-174, 2012, Cites: 2
An application of the self-organizing map to multiple view unsupervised learning
Galkowski T., Starczewski A., An application of the self-organizing map to multiple view unsupervised learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7268 LNAI, 7268 LNAI, 181-187, 2012, Cites: 1
An analytical approach to the image reconstruction problem using em algorithm
Dobosz P., An analytical approach to the image reconstruction problem using em algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 495-500, 2012, Cites: 1
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
Rutkowski L., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7269 LNCS, 7269 LNCS, 2012, Cites: 0
Preface
Rutkowski L., Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 7267 LNAI, 7267 LNAI, 2012, Cites: 0

2011 (4)

AdaBoost ensemble of DCOG rough-neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., AdaBoost ensemble of DCOG rough-neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6922 LNAI, 6922 LNAI, 62-71, 2011, Cites: 25
Rule base normalization in Takagi-Sugeno ensemble
Korytkowski M., Rutkowski L., Scherer R., Rule base normalization in Takagi-Sugeno ensemble, IEEE SSCI 2011 - Symposium Series on Computational Intelligence - HIMA 2011: 2011 IEEE Workshop on Hybrid Intelligent Models and Applications, 1-5, 2011, Cites: 3
On designing of flexible neuro-fuzzy systems for nonlinear modelling
Cpalka K., Rebrova O., Nowicki R., Rutkowski L., On designing of flexible neuro-fuzzy systems for nonlinear modelling, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6743 LNAI, 6743 LNAI, 147-154, 2011, Cites: 2
Foreword
Rutkowski L., Foreword, Intelligent Systems Reference Library, 6, 6, 2011, Cites: 0

2010 (18)

Fuzzy regression modeling for tool performance prediction and degradation detection
Li X., Er M.J., Lim B.S., Zhou J.H., Gan O.P., Rutkowski L., Fuzzy regression modeling for tool performance prediction and degradation detection, International Journal of Neural Systems, 20, 20, 405-419, 2010, Cites: 65
Online speed profile generation for industrial machine tool based on neuro-fuzzy approach
Rutkowski L., Przybyl A., Cpalka K., Er M.J., Online speed profile generation for industrial machine tool based on neuro-fuzzy approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 645-650, 2010, Cites: 53
Parallel realisation of the recurrent Elman neural network learning
Bilski J., Smolag J., Parallel realisation of the recurrent Elman neural network learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 19-25, 2010, Cites: 24
Learning methods for type-2 FLS based on FCM
Starczewski J.T., Bartczuk L., Dziwinski P., Marvuglia A., Learning methods for type-2 FLS based on FCM, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 224-231, 2010, Cites: 20
Distributed control system based on real time ethernet for computer numerical controlled machine tool
PrzybyL A., Smolag J., Kimla P., Distributed control system based on real time ethernet for computer numerical controlled machine tool, Przeglad Elektrotechniczny, 86, 86, 342-346, 2010, Cites: 16
New method for generation type-2 fuzzy partition for FDT
Bartczuk L., Dziwinski P., Starczewski J.T., New method for generation type-2 fuzzy partition for FDT, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 275-280, 2010, Cites: 16
New linguistic hedges in construction of interval type-2 FLS
Dziwinski P., Starczewski J.T., Bartczuk L., New linguistic hedges in construction of interval type-2 FLS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 445-450, 2010, Cites: 14
On non-singleton fuzzification with DCOG defuzzification
Nowicki R.K., Starczewski J.T., On non-singleton fuzzification with DCOG defuzzification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 168-174, 2010, Cites: 7
General type-2 FLS with uncertainty generated by fuzzy rough sets
Starczewski J.T., General type-2 FLS with uncertainty generated by fuzzy rough sets, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010, Cites: 6
Fault diagnosis of an air-handling unit system using a dynamic fuzzy-neural approach
Du J., Er M.J., Rutkowski L., Fault diagnosis of an air-handling unit system using a dynamic fuzzy-neural approach, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 58-65, 2010, Cites: 6
Evolutionary designing of logic-type fuzzy systems
Gabryel M., Rutkowski L., Evolutionary designing of logic-type fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 143-148, 2010, Cites: 5
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface
Rutkowski L., Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6114 LNAI, 6114 LNAI, 2010, Cites: 5
MICOG defuzzification rough-neuro-fuzzy system ensemble
Korytkowski M., Nowicki R.K., Scherer R., Rutkowski L., MICOG defuzzification rough-neuro-fuzzy system ensemble, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010, 2010, Cites: 5
An Efficient Adaptive Fuzzy Neural Network (EAFNN) approach for short term load forecasting
Du J., Er M.J., Rutkowski L., An Efficient Adaptive Fuzzy Neural Network (EAFNN) approach for short term load forecasting, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 49-57, 2010, Cites: 3
Relational type-2 interval fuzzy systems
Scherer R., Starczewski J.T., Relational type-2 interval fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6067 LNCS, 6067 LNCS, 360-368, 2010, Cites: 3
An online approach towards self-generating fuzzy neural networks with applications
Liu F., Er M.J., Rutkowski L., An online approach towards self-generating fuzzy neural networks with applications, Proceedings of the International Joint Conference on Neural Networks, 2010, Cites: 0
On automatic design of neuro-fuzzy systems
Cpalka K., Rutkowski L., Er M.J., On automatic design of neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 43-48, 2010, Cites: 0
Neural network-based assessment of femur stress after hip joint alloplasty
Korytkowski M., Rutkowski L., Scherer R., Szarek A., Neural network-based assessment of femur stress after hip joint alloplasty, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 6113 LNAI, 6113 LNAI, 621-626, 2010, Cites: 0

2009 (5)

Efficient triangular type-2 fuzzy logic systems
Starczewski J.T., Efficient triangular type-2 fuzzy logic systems, International Journal of Approximate Reasoning, 50, 50, 799-811, 2009, Cites: 70
Extended triangular norms
Starczewski J.T., Extended triangular norms, Information Sciences, 179, 179, 742-757, 2009, Cites: 33
Medical diagnosis with type-2 fuzzy decision trees
Bartczuk L., Rutkowska D., Medical diagnosis with type-2 fuzzy decision trees, Advances in Intelligent and Soft Computing, 65, 65, 11-21, 2009, Cites: 24
A type-1 approximation of interval type-2 FLS
Starczewski J.T., A type-1 approximation of interval type-2 FLS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5571 LNAI, 5571 LNAI, 287-294, 2009, Cites: 7
A new method for complexity reduction of neuro-fuzzy systems with application to differential stroke diagnosis
Cpalka K., Rebrova O., Rutkowski L., A new method for complexity reduction of neuro-fuzzy systems with application to differential stroke diagnosis, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5769 LNCS, 5769 LNCS, 435-444, 2009, Cites: 2

2008 (16)

Computational intelligence: Methods and techniques
Rutkowski L., Computational intelligence: Methods and techniques, Computational Intelligence: Methods and Techniques, 1-514, 2008, Cites: 302
From ensemble of fuzzy classifiers to single fuzzy rule base classifier
Korytkowski M., Rutkowski L., Scherer R., From ensemble of fuzzy classifiers to single fuzzy rule base classifier, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 265-272, 2008, Cites: 61
Parallel realisation of the recurrent RTRN neural network learning
Bilski J., Smolag J., Parallel realisation of the recurrent RTRN neural network learning, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 11-16, 2008, Cites: 27
Modular type-2 neuro-fuzzy systems
Starczewski J., Scherer R., Korytkowski M., Nowicki R., Modular type-2 neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 570-578, 2008, Cites: 20
Type-2 fuzzy decision trees
Bartczuk L., Rutkowska D., Type-2 fuzzy decision trees, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 197-206, 2008, Cites: 20
Ant focused crawling algorithm
Dziwinski P., Rutkowska D., Ant focused crawling algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 1018-1028, 2008, Cites: 14
Ensemble of rough-neuro-fuzzy systems for classification with missing features
Korytkowski M., Nowicki R., Scherer R., Rutkowski L., Ensemble of rough-neuro-fuzzy systems for classification with missing features, IEEE International Conference on Fuzzy Systems, 1745-1750, 2008, Cites: 14
Evolutionary methods to create interpretable modular system
Korytkowski M., Gabryel M., Rutkowski L., Drozda S., Evolutionary methods to create interpretable modular system, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 405-413, 2008, Cites: 13
On defuzzification of interval type-2 fuzzy sets
Starczewski J.T., On defuzzification of interval type-2 fuzzy sets, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 333-340, 2008, Cites: 11
Evolutionary methods for designing neuro-fuzzy modular systems combined by bagging algorithm
Gabryel M., Rutkowski L., Evolutionary methods for designing neuro-fuzzy modular systems combined by bagging algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 398-404, 2008, Cites: 10
Evolutionary learning of flexible neuro-fuzzy systems
Cpalka K., Rutkowski L., Evolutionary learning of flexible neuro-fuzzy systems, IEEE International Conference on Fuzzy Systems, 969-975, 2008, Cites: 10
Modular rough neuro-fuzzy systems for classification
Scherer R., Korytkowski M., Nowicki R., Rutkowski L., Modular rough neuro-fuzzy systems for classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4967 LNCS, 4967 LNCS, 540-548, 2008, Cites: 3
A new approach to creating multisegment fuzzy systems
Starczewski A., A new approach to creating multisegment fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 324-332, 2008, Cites: 1
An application of weighted triangular norms to complexity reduction of neuro-fuzzy systems
Cpalka K., Rutkowski L., An application of weighted triangular norms to complexity reduction of neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 207-216, 2008, Cites: 1
On differential stroke diagnosis by neuro-fuzzy structures
Cpalka K., Rebrova O., Galkowski T., Rutkowski L., On differential stroke diagnosis by neuro-fuzzy structures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 974-980, 2008, Cites: 1
Lecture Notes in Artificial Intelligence : Preface
Rutkowski L., Lecture Notes in Artificial Intelligence : Preface, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 5097 LNAI, 5097 LNAI, 2008, Cites: 0

2007 (3)

Rough-neuro-fuzzy systems for classification
Cpalka K., Nowicki R., Rutkowski L., Rough-neuro-fuzzy systems for classification, Proceedings of the 2007 IEEE Symposium on Foundations of Computational Intelligence, FOCI 2007, 1-8, 2007, Cites: 3
On obtaining fuzzy rule base from ensemble of Takagi-Sugeno systems
Korytkowski M., Rutkowski L., Scherer R., Drozda G., On obtaining fuzzy rule base from ensemble of Takagi-Sugeno systems, Proceedings of the 2007 IEEE Symposium on Computational Intelligence and Data Mining, CIDM 2007, 234-237, 2007, Cites: 1
On speeding up the learning process of neuro-fuzzy ensembles generated by the adaboost algorithm
Korytkowski M., Rutkowski L., Scherer R., On speeding up the learning process of neuro-fuzzy ensembles generated by the adaboost algorithm, Advances in Soft Computing, 45, 45, 319-326, 2007, Cites: 0

2006 (9)

On combining backpropagation with boosting
Korytkowski M., Rutkowski L., Scherer R., On combining backpropagation with boosting, IEEE International Conference on Neural Networks - Conference Proceedings, 1274-1277, 2006, Cites: 58
A new version of the fuzzy-ID3 algorithm
Bartczuk L., Rutkowska D., A new version of the fuzzy-ID3 algorithm, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 1060-1070, 2006, Cites: 23
Evolutionary learning of mamdani-type neuro-fuzzy systems
Gabryel M., Rutkowski L., Evolutionary learning of mamdani-type neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 354-359, 2006, Cites: 19
A triangular type-2 fuzzy logic system
Starczewski J.T., A triangular type-2 fuzzy logic system, IEEE International Conference on Fuzzy Systems, 1460-1467, 2006, Cites: 18
Algorithm for generating fuzzy rules for WWW document classification
Dziwinski P., Rutkowska D., Algorithm for generating fuzzy rules for WWW document classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 1111-1119, 2006, Cites: 17
A new method for designing and reduction of neuro-fuzzy systems
Cpalka K., Rutkowski L., A new method for designing and reduction of neuro-fuzzy systems, IEEE International Conference on Fuzzy Systems, 1851-1857, 2006, Cites: 16
Merging ensemble of neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Merging ensemble of neuro-fuzzy systems, IEEE International Conference on Fuzzy Systems, 1954-1957, 2006, Cites: 7
Combining logical-type neuro-fuzzy systems
Korytkowski M., Nowicki R., Rutkowski L., Scherer R., Combining logical-type neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4029 LNAI, 4029 LNAI, 240-249, 2006, Cites: 1
A new method for complexity reduction of neuro-fuzzy systems
Cpalka K., Rutkowski L., A new method for complexity reduction of neuro-fuzzy systems, WSEAS Transactions on Systems, 5, 5, 2514-2521, 2006, Cites: 1

2005 (5)

Designing and learning of adjustable quasi-triangular norms with applications to neuro-fuzzy systems
Rutkowski L., Cpalka K., Designing and learning of adjustable quasi-triangular norms with applications to neuro-fuzzy systems, IEEE Transactions on Fuzzy Systems, 13, 13, 140-151, 2005, Cites: 67
Flexible Takagi-Sugeno fuzzy systems
Cpalka K., Rutkowski L., Flexible Takagi-Sugeno fuzzy systems, Proceedings of the International Joint Conference on Neural Networks, 3, 3, 1764-1769, 2005, Cites: 56
Flexible Takagi-Sugeno neuro-fuzzy structures for nonlinear approximation
Cpalka K., Rutkowski L., Flexible Takagi-Sugeno neuro-fuzzy structures for nonlinear approximation, WSEAS Transactions on Systems, 4, 4, 1450-1458, 2005, Cites: 42
Extended triangular norms on gaussian fuzzy sets
Starczewski J.T., Extended triangular norms on gaussian fuzzy sets, Proceedings - 4th Conference of the European Society for Fuzzy Logic and Technology and 11th French Days on Fuzzy Logic and Applications, EUSFLAT-LFA 2005 Joint Conference, 872-877, 2005, Cites: 21
Flexible neuro-fuzzy structures for pattern classification
Cpalka K., Rutkowski L., Flexible neuro-fuzzy structures for pattern classification, WSEAS Transactions on Computers, 4, 4, 679-688, 2005, Cites: 7

2004 (11)

Adaptive probabilistic neural networks for pattern classification in time-varying environment
Rutkowski L., Adaptive probabilistic neural networks for pattern classification in time-varying environment, IEEE Transactions on Neural Networks, 15, 15, 811-827, 2004, Cites: 196
Generalized regression neural networks in time-varying environment
Rutkowski L., Generalized regression neural networks in time-varying environment, IEEE Transactions on Neural Networks, 15, 15, 576-596, 2004, Cites: 91
Neuro-fuzzy systems derived from quasi-triangular norms
Rutkowski L., Cpalka K., Neuro-fuzzy systems derived from quasi-triangular norms, IEEE International Conference on Fuzzy Systems, 2, 2, 1031-1036, 2004, Cites: 39
Neuro-fuzzy relational classifiers
Scherer R., Rutkowski L., Neuro-fuzzy relational classifiers, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 376-380, 2004, Cites: 23
Parallel realisation of QR algorithm for neural networks learning
Bilski J., Litwinski S., Smolag J., Parallel realisation of QR algorithm for neural networks learning, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 158-165, 2004, Cites: 20
A new method for system modelling and pattern classification
Rutkowski L., A new method for system modelling and pattern classification, Bulletin of the Polish Academy of Sciences: Technical Sciences, 52, 52, 11-24, 2004, Cites: 18
Momentum modification of the RLS algorithms
Bilski J., Momentum modification of the RLS algorithms, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 151-157, 2004, Cites: 11
What differs interval type-2 FLS from type-1 FLS?
Starczewski J.T., What differs interval type-2 FLS from type-1 FLS?, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 381-387, 2004, Cites: 7
New methods for uncertainty representations in neuro-fuzzy systems
Scherer R., Starczewski J., Gaweda A., New methods for uncertainty representations in neuro-fuzzy systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 659-667, 2004, Cites: 4
Systolic architectures for soft computing algorithms
Bilski J., Smolag J., Zurada J., Systolic architectures for soft computing algorithms, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3019, 3019, 601-608, 2004, Cites: 0
Fuzzy modelling with a compromise fuzzy reasoning
Cpalka K., Rutkowski L., Fuzzy modelling with a compromise fuzzy reasoning, Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), 3070, 3070, 284-289, 2004, Cites: 0

2003 (4)

Flexible neuro-fuzzy systems
Rutkowski L., Cpalka K., Flexible neuro-fuzzy systems, IEEE Transactions on Neural Networks, 14, 14, 554-574, 2003, Cites: 180
A Hierarchical Neuro-Fuzzy System Based on S-Implications
Nowicki R., Scherer R., Rutkowski L., A Hierarchical Neuro-Fuzzy System Based on S-Implications, Proceedings of the International Joint Conference on Neural Networks, 1, 1, 321-325, 2003, Cites: 5
Erratum: Flexible neuro-fuzzy systems (IEEE Transactions on Neural Networks (May 2003) 14 (554-574))
Rutkowski L., Cpalka K., Erratum: Flexible neuro-fuzzy systems (IEEE Transactions on Neural Networks (May 2003) 14 (554-574)), IEEE Transactions on Neural Networks, 14, 14, 967, 2003, Cites: 0
A new approach to designing fuzzy systems
Rutkowski L., Cpalka K., A new approach to designing fuzzy systems, Recent Advances in Intelligent Systems and Signal Processing, 343-347, 2003, Cites: 0

2002 (1)

Connectionist structures of type 2 fuzzy inference systems
Starczewski J., Rutkowski L., Connectionist structures of type 2 fuzzy inference systems, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2328, 2328, 634-642, 2002, Cites: 62

1998 (1)

A fast training algorithm for neural networks
Bilski J., Rutkowski L., A fast training algorithm for neural networks, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 45, 45, 749-753, 1998, Cites: 64

1986 (1)

Nonparametric Fitting of Multivariate Functions
Galkowski T., Rutkowski L., Nonparametric Fitting of Multivariate Functions, IEEE Transactions on Automatic Control, 31, 31, 785-787, 1986, Cites: 63

1985 (1)

Nonparametric Recovery of Multivariate Functions with Applications to System Identification
Galkowski T., Rutkowski L., Nonparametric Recovery of Multivariate Functions with Applications to System Identification, Proceedings of the IEEE, 73, 73, 942-943, 1985, Cites: 61

1983 (1)

NEW ALGORITHM FOR SHAPE ANALYSIS - THE MULTIDIMENSIONAL CASE.
Galkowski Tomasz, Rutkowski Leszek, NEW ALGORITHM FOR SHAPE ANALYSIS - THE MULTIDIMENSIONAL CASE., 49-53, 1983, Cites: 0