Hierarchical discrete systems and realisation of parallel algorithms. - Nikola K. Kasabov; G. T. Bijev; B. J. Jechev (CONPAR, 1981)

A method for SIMD/MIMD functionally reconfigurable multimicroprocessor systems design and parallel data exchange algorithms. - Nikola K. Kasabov (Parallel Comput., 1985)

Functionally reconfigurable general purpose parallel machines and some image processing and pattern recognition applications. - Nikola K. Kasabov (Pattern Recognit. Lett., 1985)

Hybrid Connectionist Rule-Based Systems. - Nikola K. Kasabov (AIMSA, 1990)

Prognostic Expert Systems on a Hybrid Connectionist Environment. - Nikola K. Kasabov; Daniel Nikovski (AIMSA, 1992)

Neural Networks and Logic Programming - a Hybrid Model and its Applicability to Building Expert Systems. - Nikola K. Kasabov; S. H. Petkov (ECAI, 1992)

Learning fuzzy rules through neural networks. - Nikola K. Kasabov (ANNES, 1993)

Connectionist expert systems. - Nikola K. Kasabov; Lakhmi C. Jain (ANNES, 1993)

Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems. - Nikola K. Kasabov; Daniel Nikovski; Emilian Peev (ANNES, 1993)

Connectionist Fuzzy Production Systems. - Nikola K. Kasabov (Fuzzy Logic in Artificial Intelligence, 1993)

Hybrid Connectionist Fuzzy Systems for Speech Recognition and the Use of Connectionist Production Systems. - Nikola K. Kasabov (IEEE/Nagoya-University World Wisepersons Workshop, 1994)

Hybrid Systems for Prediction - A Case Study of Predicting Effluent Flow to a Sewage Plant. - Max Bailey; Nikola K. Kasabov; Peter Mason; Andrew R. Gray; Tico Cohen (ANNES, 1995)

Hybrid Systems for Medical Data Analysis and Decision Making - A Case Study on Varicose Vein Disorders . - Max Bailey; Clive Solomon; Nikola K. Kasabov; Simon Greig (ANNES, 1995)

Intelligent human computer interfaces and the case study of building English-to-Maori talking dictionary. - Nikola K. Kasabov; S. J. Sinclair; Richard Kilgour; Catherine I. Watson; Mark R. Laws; Diana Kassabova (ANNES, 1995)

Hybrid Connectionist Fuzzy Production System: Towards Building Comprehensive AI. - Nikola K. Kasabov (Intell. Autom. Soft Comput., 1995)

Model for exploiting associative matching in AI production systems. - Nikola K. Kasabov; Simon H. Lavington; S. Lin; C. Wang (Knowl. Based Syst., 1995)

Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems. - Nikola K. Kasabov (Fuzzy Sets Syst., 1996)

Preface. - Nikola K. Kasabov; Takeshi Yamakawa (Fuzzy Sets Syst., 1996)

Adaptable neuro production systems. - Nikola K. Kasabov (Neurocomputing, 1996)

Fril - Fuzzy and Evidential Reasoning in Artificial Intelligence, by J. F. Baldwin, T. P. Martin, and B. W. Pilsworth. - Nikola K. Kasabov (J. Am. Soc. Inf. Sci., 1996)

Fuzzy rules extraction, reasoning and rules adaptation in fuzzy neural networks. - Nikola K. Kasabov (ICNN, 1997)

Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks. - Nikola K. Kasabov; Michael J. Watts (ICNN, 1997)

An Agent Based Framework for Modular Speech Recognition and Language Processing Systems. - Andrew R. Gray; Richard Kilgour; Nikola K. Kasabov (ICONIP (2), 1997)

A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks. - Nikola K. Kasabov; Robert Kozma 001; Richard Kilgour; Mark R. Laws; J. Taylor; Michael J. Watts; Andrew R. Gray (ICONIP (2), 1997)

Neuro-Fuzzy and Multivariate Statistical Classification of Fruit Populations Based on Visible-Near Infrared Spectrophotometry Data. - Jaesoo Kim; A. Mowat; P. Poole; Nikola K. Kasabov (ICONIP (2), 1997)

Multi-Agent Implementation of Fractal Analysis by Fuzzy Neural Networks. - Robert Kozma 001; J. A. Swope; Nikola K. Kasabov; M. J. A. Williams (ICONIP (1), 1997)

Adaptive Training of Radial Basis Function Networks Based on Cooperative Evolution and Evolutionary Programming. - Alexander P. Topchy; Oleg A. Lebedko; Victor V. Miagkikh; Nikola K. Kasabov (ICONIP (1), 1997)

A Membership Function Selection Method for Fuzzy Neural Networks. - Quingqing Zhou; Martin K. Purvis; Nikola K. Kasabov (ICONIP (2), 1997)

Special Issue on Advanced Neuro-Fuzzy Techniques and Their Applications: Introduction. - Nikola K. Kasabov; Kaoru Hirota (Inf. Sci., 1997)

FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition. - Nikola K. Kasabov; Jaesoo Kim; Michael J. Watts; Andrew R. Gray (Inf. Sci., 1997)

Statistical, connectionist, and fuzzy inference techniques for image classification. - Steven A. Israel; Nikola K. Kasabov (J. Electronic Imaging, 1997)

Learning Strategies for Modular Neuro-Fuzzy Systems: A Case Study on Phoneme-Based Speech Recognition. - Nikola K. Kasabov (J. Intell. Fuzzy Syst., 1997)

Evolving Connectionist Systems and Evolving Brains. - Nikola K. Kasabov (ICONIP, 1998)

ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm. - Nikola K. Kasabov (ICONIP, 1998)

Genetic Algorithms for the Design of Fuzzy Neural Networks. - Michael J. Watts; Nikola K. Kasabov (ICONIP, 1998)

Enhancing recognition systems through an integrated processing of visual and audio information. - Eric O. Postma; Nikola K. Kasabov; H. Jaap van den Herik (SMC, 1998)

Introduction: Hybrid intelligent adaptive systems. - Nikola K. Kasabov; Robert Kozma 001 (Int. J. Intell. Syst., 1998)

Hybrid intelligent adaptive systems: A framework and a case study on speech recognition. - Nikola K. Kasabov; Robert Kozma 001 (Int. J. Intell. Syst., 1998)

Integration of connectionist methods and chaotic time-series analysis for the prediction of process data. - Robert Kozma 001; Nikola K. Kasabov; Jaesoo Kim; Tico Cohen (Int. J. Intell. Syst., 1998)

Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning. - Nikola K. Kasabov; Robert Kozma 001; Michael J. Watts (Inf. Sci., 1998)

The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems. - Nikola K. Kasabov (J. Adv. Comput. Intell. Intell. Informatics, 1998)

Editorial: Self-Organization and Adaptation in Intelligent Systems. - Nikola K. Kasabov; Robert Kozma 001 (J. Adv. Comput. Intell. Intell. Informatics, 1998)

Evolving connectionist systems: A theory and a case study on adaptive speech recognition. - Nikola K. Kasabov (IJCNN, 1999)

From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition. - Nikola K. Kasabov; Richard Kilgour; S. J. Sinclair (Fuzzy Sets Syst., 1999)

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. - Jaesoo Kim; Nikola K. Kasabov (Neural Networks, 1999)

Evolving Fuzzy Neural Network for Camera Operations Recognition. - Irena Koprinska; Nikola K. Kasabov (ICPR, 2000)

ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams. - Da Deng 001; Nikola K. Kasabov (IJCNN (6), 2000)

Hybrid System for Robust Recognition of Noisy Speech Based on Evolving Fuzzy Neural Networks and Adaptive Filtering. - Nikola K. Kasabov; Georgi Iliev (IJCNN (5), 2000)

Methods and systems for intelligent human-computer interaction. - Nikola K. Kasabov; Robert Kozma 001 (Inf. Sci., 2000)

AVIS: a connectionist-based framework for integrated auditory and visual information processing. - Nikola K. Kasabov; Eric O. Postma; H. Jaap van den Herik (Inf. Sci., 2000)

The Application of Hybrid Evolving Connectionist Systems to Image Classification. - Nikola K. Kasabov; Steven A. Israel; Brendon J. Woodford (J. Adv. Comput. Intell. Intell. Informatics, 2000)

Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategy. - Michael J. Watts; Nikola K. Kasabov (CEC, 2001)

Ensembles of EFuNNs: An Architecture for a Mutlimodule Classifier. - Brendon J. Woodford; Nikola K. Kasabov (FUZZ-IEEE, 2001)

An evolving localised learning model for on-line image colour quantisation. - Da Deng 001; Nikola K. Kasabov (ICIP (1), 2001)

On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks. - Nikola K. Kasabov (Neurocomputing, 2001)

Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application. - Nikola K. Kasabov; Jaesoo Kim; Robert Kozma 001; Tico Cohen (J. Adv. Comput. Intell. Intell. Informatics, 2001)

Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning. - Nikola K. Kasabov (IEEE Trans. Syst. Man Cybern. Part B, 2001)

Evolutionary optimisation of evolving connectionist systems. - Michael J. Watts; Nikola K. Kasabov (IEEE Congress on Evolutionary Computation, 2002)

Fuzzy clustering of gene expression data. - Matthias E. Futschik; Nikola K. Kasabov (FUZZ-IEEE, 2002)

DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. - Nikola K. Kasabov; Qun Song 002 (IEEE Trans. Fuzzy Syst., 2002)

A Generic Connectionist-Based Method for On-Line Feature Selection and Modelling with a Case Study of Gene Expression Data Analysis. - Nikola K. Kasabov; Melanie Middlemiss; T. Lane (APBC, 2003)

Integrated gene expression analysis of multiple microarray data sets based on a normalization technique and on adaptive connectionist model. - Liang Goh; Nikola K. Kasabov (IJCNN, 2003)

Evolutionary computation for dynamic parameter optimisation of evolving connectionist systems for on-line prediction of time series with changing dynamics. - Nikola K. Kasabov; Qun Song 002; Ikuko Nishikanawa (IJCNN, 2003)

Neural systems for solving the inverse problem of recovering the primary signal waveform in potential transformers. - Nikola K. Kasabov; Gancho Venkov; Stefan Minchev (IJCNN, 2003)

Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue. - Matthias E. Futschik; Anthony Reeve; Nikola K. Kasabov (Artif. Intell. Medicine, 2003)

Simulation of ECB decisions and forecast of short term Euro rate with an adaptive fuzzy expert system. - Lorenzo Rizzi; Flavio Bazzana; Nikola K. Kasabov; Mario Fedrizzi; Luca Erzegovesi (Eur. J. Oper. Res., 2003)

On-line pattern analysis by evolving self-organizing maps. - Da Deng 001; Nikola K. Kasabov (Neurocomputing, 2003)

Reduced feature-set based parallel CHMM speech recognition systems. - Waleed H. Abdulla; Nikola K. Kasabov (Inf. Sci., 2003)

Adaptive speech recognition with evolving connectionist systems. - Akbar Ghobakhlou; Michael J. Watts; Nikola K. Kasabov (Inf. Sci., 2003)

Spoken language analysis, modeling and recognition - Cstatistical and adaptive connectionist approaches. - Nikola K. Kasabov (Inf. Sci., 2003)

Modeling the emergence of bilingual acoustic clusters: a preliminary case study. - Mark R. Laws; Richard Kilgour; Nikola K. Kasabov (Inf. Sci., 2003)

A Novel Feature Selection Method to Improve Classification of Gene Expression Data. - Liang Goh; Qun Song 002; Nikola K. Kasabov (APBC, 2004)

Discovering Rules of Adaptation and Interaction: From Molecules and Gene Interaction to Brain Functions. - Nikola K. Kasabov (HIS, 2004)

An adaptive model of person identification combining speech and image information. - David Zhang; Akbar Ghobakhlou; Nikola K. Kasabov (ICARCV, 2004)

One-Pass Incremental Membership Authentication by Face Classification. - Shaoning Pang 001; Seiichi Ozawa; Nikola K. Kasabov (ICBA, 2004)

An Evolving Neural Network Model for Person Verification Combining Speech and Image. - Akbar Ghobakhlou; David Zhang; Nikola K. Kasabov (ICONIP, 2004)

Gene Regulatory Network Discovery from Time-Series Gene Expression Data - A Computational Intelligence Approach. - Nikola K. Kasabov; Zeke S. H. Chan; Vishal Jain; Igor Sidorov 001; Dimiter S. Dimitrov (ICONIP, 2004)

Dynamic Neuro-fuzzy Inference and Statistical Models for Risk Analysis of Pest Insect Establishment. - Snjezana Soltic; Shaoning Pang 001; Nikola K. Kasabov; Susan P. Worner; Lora Peacock (ICONIP, 2004)

TWRBF - Transductive RBF Neural Network with Weighted Data Normalization. - Qun Song 002; Nikola K. Kasabov (ICONIP, 2004)

Gene trajectory clustering with a hybrid genetic algorithm and expectation maximization method. - Zeke S. H. Chan; Nikola K. Kasabov (IJCNN, 2004)

Computational neurogenetic modelling: gene networks within neural networks. - Nikola K. Kasabov; Lubica Benuskova; Simei Gomes Wysoski (IJCNN, 2004)

Inductive vs transductive inference, global vs local models: SVM, TSVM, and SVMT for gene expression classification problems. - Shaoning Pang 001; Nikola K. Kasabov (IJCNN, 2004)

WDN-RBF: weighted data normalization for radial basic function type neural networks. - Qun Song 002; Nikola K. Kasabov (IJCNN, 2004)

A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier. - Seiichi Ozawa; Shaoning Pang 001; Nikola K. Kasabov (PRICAI, 2004)

Evolutionary Computation For On-Line And Off-Line Parameter Tuning Of Evolving Fuzzy Neural Networksc. - Zeke S. H. Chan; Nikola K. Kasabov (Int. J. Comput. Intell. Appl., 2004)

A Methodology and a System for Adaptive, Integrated Speech and Image Learning and Recognition. - Akbar Ghobakhlou; Nikola K. Kasabov (Int. J. Comput. Syst. Signals, 2004)

Editorial. - Nikola K. Kasabov; Shaoning Pang 001 (Int. J. Comput. Syst. Signals, 2004)

Evolving Connectionist Systems Based Role Allocation of Robots for Soccer Playing. - L. Huang; Qun Song 002; Nikola K. Kasabov (ISIC, 2005)

TWNFC - Transductive Neural-Fuzzy Classifier with Weighted Data Normalization and Its Application in Medicine. - Tianmin Ma; Qun Song 002; Nikola K. Kasabov; Mark Roger Marshall (CIMCA/IAWTIC, 2005)

Transductive Knowledge Based Fuzzy Inference System for Personalized Modeling. - Qun Song 002; Tianmin Ma; Nikola K. Kasabov (FSKD (2), 2005)

Computational Neurogenetic Modeling: Integration of Spiking Neural Networks, Gene Networks, and Signal Processing Techniques. - Nikola K. Kasabov; Lubica Benuskova; Simei Gomes Wysoski (ICANN (2), 2005)

A computational neurogenetic model of a spiking neuron. - Nikola K. Kasabov; Lubica Benuskova; Simei Gomes Wysoski (IJCNN, 2005)

Transductive modeling with GA parameter optimization. - Nisha Mohan; Nikola K. Kasabov (IJCNN, 2005)

Incremental learning for online face recognition. - Seiichi Ozawa; Soon Lee Toh; Shigeo Abe; Shaoning Pang 001; Nikola K. Kasabov (IJCNN, 2005)

Chunk Incremental LDA Computing on Data Streams. - Shaoning Pang 001; Seiichi Ozawa; Nikola K. Kasabov (ISNN (2), 2005)

Global EM Learning of Finite Mixture Models using the Greedy Elimination Method. - Zeke S. H. Chan; Nikola K. Kasabov (SGAI Conf., 2005)

Fast Estimation of Distribution Algorithm (EDA) via Constrained Multi-Parent Recombination. - Zeke S. H. Chan; Nikola K. Kasabov (SGAI Conf., 2005)

Computational Intelligence for Bioinformatics: The Knowledge Engineering Approach. - Nikola K. Kasabov (SGAI Conf., 2005)

Introduction. - Nikola K. Kasabov; Hojjat Adeli; Nikhil R. Pal (Int. J. Neural Syst., 2005)

A Hybrid Genetic Algorithm and Expectation Maximization Method for Global Gene Trajectory Clustering. - Zeke S. H. Chan; Nikola K. Kasabov; Lesley Collins (J. Bioinform. Comput. Biol., 2005)

An Integrated Feature Selection and Classification Method to Select Minimum Number of Variables on the Case Study of Gene Expression Data. - Liang Goh; Nikola K. Kasabov (J. Bioinform. Comput. Biol., 2005)

Incremental learning of feature space and classifier for face recognition. - Seiichi Ozawa; Soon Lee Toh; Shigeo Abe; Shaoning Pang 001; Nikola K. Kasabov (Neural Networks, 2005)

A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD). - Zeke S. H. Chan; Nikola K. Kasabov (Neural Process. Lett., 2005)

NFI: a neuro-fuzzy inference method for transductive reasoning. - Qun Song 002; Nikola K. Kasabov (IEEE Trans. Fuzzy Syst., 2005)

Fast neural network ensemble learning via negative-correlation data correction. - Zeke S. H. Chan; Nikola K. Kasabov (IEEE Trans. Neural Networks, 2005)

Incremental linear discriminant analysis for classification of data streams. - Shaoning Pang 001; Seiichi Ozawa; Nikola K. Kasabov (IEEE Trans. Syst. Man Cybern. Part B, 2005)

Evolving ontologies for intelligent decision support. - Paulo C. M. Gottgtroy; Nikola K. Kasabov; Stephen G. MacDonell (Fuzzy Logic and the Semantic Web, 2006)

Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (ACIVS, 2006)

TTLSC - Transductive Total Least Square Model for Classification and Its Application in Medicine. - Qun Song 002; Tianmin Ma; Nikola K. Kasabov (ADMA, 2006)

An Incremental Principal Component Analysis for Chunk Data. - Seiichi Ozawa; Shaoning Pang 001; Nikola K. Kasabov (FUZZ-IEEE, 2006)

Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries. - Nikola K. Kasabov; Vishal Jain; Paulo C. M. Gottgtroy; Lubica Benuskova; Frances Joseph (HIS, 2006)

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (ICANN (1), 2006)

Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations. - Lubica Benuskova; Simei Gomes Wysoski; Nikola K. Kasabov (IJCNN, 2006)

Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis. - Shaoning Pang 001; Ilkka Havukkala; Nikola K. Kasabov (ISNN (2), 2006)

Investigating LLE Eigenface on Pose and Face Identification. - Shaoning Pang 001; Nikola K. Kasabov (ISNN (2), 2006)

Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery. - Ilkka Havukkala; Lubica Benuskova; Shaoning Pang 001; Vishal Jain; Rene Kroon; Nikola K. Kasabov (PRIB, 2006)

Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation. - Qun Song 002; Nikola K. Kasabov; Tianmin Ma; Mark Roger Marshall (Artif. Intell. Medicine, 2006)

Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems. - Nikola K. Kasabov (Appl. Soft Comput., 2006)

An efficient greedy K-means algorithm for global gene trajectory clustering. - Zeke S. H. Chan; Lesley Collins; Nikola K. Kasabov (Expert Syst. Appl., 2006)

A two-stage methodology for gene regulatory network extraction from time-course gene expression data. - Zeke S. H. Chan; Nikola K. Kasabov; Lesley Collins (Expert Syst. Appl., 2006)

Computational Neurogenetic Modelling: a Pathway to New Discoveries in Genetic Neuroscience. - Lubica Benuskova; Vishal Jain; Simei Gomes Wysoski; Nikola K. Kasabov (Int. J. Neural Syst., 2006)

Short-term ANN load forecasting from limited data using generalization learning strategies. - Zeke S. H. Chan; H. W. Ngan; Ahmad B. Rad; A. K. David; Nikola K. Kasabov (Neurocomputing, 2006)

Incremental learning of feature space and classifier for on-line pattern recognition. - Seiichi Ozawa; Shaoning Pang 001; Nikola K. Kasabov (Int. J. Knowl. Based Intell. Eng. Syst., 2006)

TWNFI - a transductive neuro-fuzzy inference system with weighted data normalization for personalized modeling. - Qun Song 002; Nikola K. Kasabov (Neural Networks, 2006)

Evolving connectionist systems - the knowledge engineering approach (2. ed.). - Nikola K. Kasabov (Springer, 2007)

A versatile quantum-inspired evolutionary algorithm. - Michael Defoin-Platel; Stefan Schliebs; Nikola K. Kasabov (IEEE Congress on Evolutionary Computation, 2007)

Evolving Connectionist and Hybrid Systems: Methods, Tools, Applications. - Nikola K. Kasabov (HIS, 2007)

Text-Independent Speaker Authentication with Spiking Neural Networks. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (ICANN (2), 2007)

Evolving Connectionist Systems for Adaptive Sport Coaching. - Boris Bacic; Nikola K. Kasabov; Stephen G. MacDonell; Shaoning Pang 001 (ICONIP (2), 2007)

Ontology-Based Framework for Personalized Diagnosis and Prognosis of Cancer Based on Gene Expression Data. - Yingjie Hu; Nikola K. Kasabov (ICONIP (2), 2007)

Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis. - Seiichi Ozawa; Shaoning Pang 001; Nikola K. Kasabov (ICONIP (2), 2007)

Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (ICONIP (2), 2007)

Evolving Brain-Gene Ontology System (EBGOS): Towards Integrating Bioinformatics and Neuroinformatics Data to Facilitate Discoveries. - Nikola K. Kasabov; Vishal Jain; Paulo C. M. Gottgtroy; Lubica Benuskova; Simei Gomes Wysoski; Frances Joseph (IJCNN, 2007)

Bayesian learning of sparse gene regulatory networks. - Zeke S. H. Chan; Lesley Collins; Nikola K. Kasabov (Biosyst., 2007)

Brain Gene Ontology and Simulation System (bgos) for a Better Understanding of the Brain. - Nikola K. Kasabov; Vishal Jain; Paulo C. M. Gottgtroy; Lubica Benuskova; Frances Joseph (Cybern. Syst., 2007)

Modeling L-LTP based on changes in concentration of pCREB transcription factor. - Lubica Benuskova; Nikola K. Kasabov (Neurocomputing, 2007)

Classification consistency analysis for bootstrapping gene selection. - Shaoning Pang 001; Ilkka Havukkala; Yingjie Hu; Nikola K. Kasabov (Neural Comput. Appl., 2007)

Global, local and personalised modeling and pattern discovery in bioinformatics: An integrated approach. - Nikola K. Kasabov (Pattern Recognit. Lett., 2007)

Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities. - Nikola K. Kasabov (Challenges for Computational Intelligence, 2007)

MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules. - Yuan-Chun Hwang; Qun Song 002; Nikola K. Kasabov (FUZZ-IEEE, 2008)

Vision Based Mobile Robot for Indoor Environmental Security. - Sean W. Gordon; Shaoning Pang 001; Ryota Nishioka; Nikola K. Kasabov; Takeshi Yamakawa (ICONIP (1), 2008)

A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems. - Masayuki Hisada; Seiichi Ozawa; Kau Zhang; Shaoning Pang 001; Nikola K. Kasabov (ICONIP (1), 2008)

Personalized Modeling Based Gene Selection for Microarray Data Analysis. - Yingjie Hu; Qun Song 002; Nikola K. Kasabov (ICONIP (1), 2008)

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework. - Nikola K. Kasabov (ICONIP (1), 2008)

Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio. - Seiichi Ozawa; Kazuya Matsumoto; Shaoning Pang 001; Nikola K. Kasabov (ICONIP (1), 2008)

Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network. - Stefan Schliebs; Michael Defoin-Platel; Nikola K. Kasabov (ICONIP (1), 2008)

Personalised Modelling for Multiple Time-Series Data Prediction: A Preliminary Investigation in Asia Pacific Stock Market Indexes Movement. - Harya Widiputra; Russel Pears; Nikola K. Kasabov (ICONIP (1), 2008)

r-SVMT: Discovering the knowledge of association rule over SVM classification trees. - Shaoning Pang 001; Nikola K. Kasabov (IJCNN, 2008)

Evolving spiking neural networks for taste recognition. - Snjezana Soltic; Simei Gomes Wysoski; Nikola K. Kasabov (IJCNN, 2008)

Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data. - Zeke S. H. Chan; Ilkka Havukkala; Vishal Jain; Yingjie Hu; Nikola K. Kasabov (Appl. Soft Comput., 2008)

Evolving Intelligence in Humans and Machines: Integrative Evolving Connectionist Systems Approach. - Nikola K. Kasabov (IEEE Comput. Intell. Mag., 2008)

Adaptive modeling and discovery in bioinformatics: The evolving connectionist approach. - Nikola K. Kasabov (Int. J. Intell. Syst., 2008)

Fast and adaptive network of spiking neurons for multi-view visual pattern recognition. - Simei Gomes Wysoski; Lubica Benusková; Nikola K. Kasabov (Neurocomputing, 2008)

Integrating evolving brain-gene ontology and connectionist-based system for modeling and knowledge discovery. - Nikola K. Kasabov; Vishal Jain; Lubica Benuskova (Neural Networks, 2008)

Guest Editorial Evolving Fuzzy Systems - Preface to the Special Section. - Plamen Angelov 001; Dimitar P. Filev; Nikola K. Kasabov (IEEE Trans. Fuzzy Syst., 2008)

Incremental Learning of Chunk Data for Online Pattern Classification Systems. - Seiichi Ozawa; Shaoning Pang 001; Nikola K. Kasabov (IEEE Trans. Neural Networks, 2008)

Integration of Brain-Gene Ontology and Simulation Systems for Learning, Modelling and Discovery. - Nikola K. Kasabov; Vishal Jain; Lubica Benuskova; Paulo C. M. Gottgtroy; Frances Joseph (Computational Intelligence in Medical Informatics, 2008)

Integrating Local and Personalised Modelling with Global Ontology Knowledge Bases for Biomedical and Bioinformatics Decision Support. - Nikola K. Kasabov; Qun Song 002; Lubica Benuskova; Paulo C. M. Gottgtroy; Vishal Jain; Anju Verma; Ilkka Havukkala; Elaine Rush; Russel Pears; Alex Tjahjana; Yingjie Hu; Stephen G. MacDonell (Computational Intelligence in Biomedicine and Bioinformatics, 2008)

SVMT-Rule: Association Rule Mining Over SVM Classification Trees. - Shaoning Pang 001; Nikola K. Kasabov (Rule Extraction from Support Vector Machines, 2008)

Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data. - Maurizio Fiasché; Anju Verma; Maria Cuzzola; Pasquale Iacopino; Nikola K. Kasabov; Francesco Carlo Morabito (ICANN (2), 2009)

Spanning SVM Tree for Personalized Transductive Learning. - Shaoning Pang 001; Tao Ban; Youki Kadobayashi; Nikola K. Kasabov (ICANN (1), 2009)

Hierarchical Core Vector Machines for Network Intrusion Detection. - Ye Chen; Shaoning Pang 001; Nikola K. Kasabov; Tao Ban; Youki Kadobayashi (ICONIP (2), 2009)

String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization. - Haza Nuzly Abdull Hamed; Nikola K. Kasabov; Zbynek Michlovský; Siti Mariyam Hj. Shamsuddin (ICONIP (2), 2009)

Coevolutionary Method for Gene Selection and Parameter Optimization in Microarray Data Analysis. - Yingjie Hu; Nikola K. Kasabov (ICONIP (2), 2009)

String Kernel Based SVM for Internet Security Implementation. - Zbynek Michlovský; Shaoning Pang 001; Nikola K. Kasabov; Tao Ban; Youki Kadobayashi (ICONIP (2), 2009)

Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach. - Anju Verma; Maurizio Fiasché; Maria Cuzzola; Pasquale Iacopino; Francesco Carlo Morabito; Nikola K. Kasabov (ICONIP (2), 2009)

A Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction. - Harya Widiputra; Henry Kho; Lukas; Russel Pears; Nikola K. Kasabov (ICONIP (2), 2009)

Adaptive incremental principal component analysis in nonstationary online learning environments. - Seiichi Ozawa; Yuki Kawashima; Shaoning Pang 001; Nikola K. Kasabov (IJCNN, 2009)

Curiosity driven incremental LDA agent active learning. - Shaoning Pang 001; Seiichi Ozawa; Nikola K. Kasabov (IJCNN, 2009)

Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling. - Stefan Schliebs; Michael Defoin-Platel; Susan P. Worner; Nikola K. Kasabov (IJCNN, 2009)

Integrated Feature Selection and Parameter Optimization for Evolving Spiking Neural Networks Using Quantum Inspired Particle Swarm Optimization. - Haza Nuzly Abdull Hamed; Nikola K. Kasabov; Siti Mariyam Shamsuddin (SoCPaR, 2009)

Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach. - Anju Verma; Nikola K. Kasabov; Elaine Rush; Qun Song 002 (Aust. J. Intell. Inf. Process. Syst., 2009)

Dynamic interaction networks in modelling and predicting the behaviour of multiple interactive stock markets. - Harya Widiputra; Russel Pears; Antoaneta Serguieva; Nikola K. Kasabov (Intell. Syst. Account. Finance Manag., 2009)

Encoding and decoding the knowledge of association rules over SVM classification trees. - Shaoning Pang 001; Nikola K. Kasabov (Knowl. Inf. Syst., 2009)

Integrative connectionist learning systems inspired by nature: current models, future trends and challenges. - Nikola K. Kasabov (Nat. Comput., 2009)

Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models. - Stefan Schliebs; Michael Defoin-Platel; Susan P. Worner; Nikola K. Kasabov (Neural Networks, 2009)

Quantum-Inspired Evolutionary Algorithm: A Multimodel EDA. - Michael Defoin-Platel; Stefan Schliebs; Nikola K. Kasabov (IEEE Trans. Evol. Comput., 2009)

Factorizing Class Characteristics via Group MEBs Construction. - Ye Chen; Shaoning Pang 001; Nikola K. Kasabov (ICONIP (2), 2010)

Tuning N-gram String Kernel SVMs via Meta Learning. - Nuwan Gunasekara; Shaoning Pang 001; Nikola K. Kasabov (ICONIP (2), 2010)

Towards Spatio-Temporal Pattern Recognition Using Evolving Spiking Neural Networks. - Stefan Schliebs; Nuttapod Nuntalid; Nikola K. Kasabov (ICONIP (1), 2010)

Incremental and decremental LDA learning with applications. - Shaoning Pang 001; Tao Ban; Youki Kadobayashi; Nikola K. Kasabov (IJCNN, 2010)

Analyzing the dynamics of the simultaneous feature and parameter optimization of an evolving Spiking Neural Network. - Stefan Schliebs; Michael Defoin-Platel; Nikola K. Kasabov (IJCNN, 2010)

Evolving Integrative Brain-, Gene-, and Quantum Inspired Systems for Computational Intelligence and Knowledge Engineering. - Nikola K. Kasabov (KES (1), 2010)

Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis: A Computational Framework Proposed. - Maurizio Fiasché; Maria Cuzzola; Pasquale Iacopino; Nikola K. Kasabov; Francesco Carlo Morabito (Aust. J. Intell. Inf. Process. Syst., 2010)

Probabilistic Evolving Spiking Neural Network Optimization Using Dynamic Quantum-inspired Particle Swarm Optimization. - Haza Nuzly Abdull Hamed; Nikola K. Kasabov; Siti Mariyam Shamsuddin (Aust. J. Intell. Inf. Process. Syst., 2010)

Editorial. - Plamen Angelov 001; Dimitar P. Filev; Nikola K. Kasabov (Evol. Syst., 2010)

Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems. - Masayuki Hisada; Seiichi Ozawa; Kau Zhang; Nikola K. Kasabov (Evol. Syst., 2010)

Integrated optimisation method for personalised modelling and case studies for medical decision support. - Nikola K. Kasabov; Yingjie Hu (Int. J. Funct. Informatics Pers. Medicine, 2010)

On the Probabilistic Optimization of Spiking Neural Networks. - Stefan Schliebs; Nikola K. Kasabov; Michael Defoin-Platel (Int. J. Neural Syst., 2010)

Knowledge Extraction from Evolving Spiking Neural Networks with Rank Order Population Coding. - Snjezana Soltic; Nikola K. Kasabov (Int. J. Neural Syst., 2010)

To spike or not to spike: A probabilistic spiking neuron model. - Nikola K. Kasabov (Neural Networks, 2010)

Evolving spiking neural networks for audiovisual information processing. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (Neural Networks, 2010)

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework. - Nikola K. Kasabov (Advances in Machine Learning II, 2010)

Effective and Adaptive Learning Based on Diversive/Specific Curiosity. - Naoki Shimo; Shaoning Pang 001; Keiichi Horio; Nikola K. Kasabov; Hakaru Tamukoh; Takanori Koga; Satoshi Sonoh; Hirohisa Isogai; Takeshi Yamakawa (Brain-Inspired Information Technology, 2010)

Brain-Like Evolving Spiking Neural Networks for Multimodal Information Processing. - Simei Gomes Wysoski; Lubica Benuskova; Nikola K. Kasabov (Brain-Inspired Information Technology, 2010)

Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling. - Nikola K. Kasabov; Stefan Schliebs; Ammar Mohemmed (CIBB, 2011)

Personalised Modelling on SNPs Data for Crohn's Disease Prediction. - Yingjie Hu; Nikola K. Kasabov (ICONIP (1), 2011)

Evolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition. - Nikola K. Kasabov; Kshitij Dhoble; Nuttapod Nuntalid; Ammar Mohemmed (ICONIP (3), 2011)

Exploring Associations between Changes in Ambient Temperature and Stroke Occurrence: Comparative Analysis Using Global and Personalised Modelling Approaches. - Wen Liang; Yingjie Hu; Nikola K. Kasabov; Valery Feigin (ICONIP (1), 2011)

SPAN: A Neuron for Precise-Time Spike Pattern Association. - Ammar Mohemmed; Stefan Schliebs; Nikola K. Kasabov (ICONIP (2), 2011)

EEG Classification with BSA Spike Encoding Algorithm and Evolving Probabilistic Spiking Neural Network. - Nuttapod Nuntalid; Kshitij Dhoble; Nikola K. Kasabov (ICONIP (1), 2011)

Reservoir-Based Evolving Spiking Neural Network for Spatio-temporal Pattern Recognition. - Stefan Schliebs; Haza Nuzly Abdull Hamed; Nikola K. Kasabov (ICONIP (2), 2011)

Method for Training a Spiking Neuron to Associate Input-Output Spike Trains. - Ammar Mohemmed; Stefan Schliebs; Satoshi Matsuda; Nikola K. Kasabov (EANN, 2011)

An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification. - Haza Nuzly Abdull Hamed; Nikola K. Kasabov; Siti Mariyam Shamsuddin; Harya Widiputra; Kshitij Dhoble (IJCNN, 2011)

Optimization of Spiking Neural Networks with dynamic synapses for spike sequence generation using PSO. - Ammar Mohemmed; Satoshi Matsuda; Stefan Schliebs; Kshitij Dhoble; Nikola K. Kasabov (IJCNN, 2011)

Are probabilistic spiking neural networks suitable for reservoir computing? - Stefan Schliebs; Ammar Mohemmed; Nikola K. Kasabov (IJCNN, 2011)

Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends. - Harya Widiputra; Russel Pears; Nikola K. Kasabov (PAKDD (2), 2011)

Dynamic Interaction Networks versus Local Trend Models for Multiple Time-Series Prediction. - Harya Widiputra; Russel Pears; Nikola K. Kasabov (Cybern. Syst., 2011)

Personalized mode transductive spanning SVM classification tree. - Shaoning Pang 001; Tao Ban; Youki Kadobayashi; Nikola K. Kasabov (Inf. Sci., 2011)

Correlation-aided support vector regression for forex time series prediction. - Shaoning Pang 001; Lei Song; Nikola K. Kasabov (Neural Comput. Appl., 2011)

Guest Editorial Special Issue on Computational Modeling of Neural and Brain Development. - Yaochu Jin; Yan Meng 002; Juyang Weng; Nikola K. Kasabov (IEEE Trans. Auton. Ment. Dev., 2011)

Probabilistic Computational Neurogenetic Modeling: From Cognitive Systems to Alzheimer's Disease. - Nikola K. Kasabov; Reinhard Schliebs; Hiroshi Kojima (IEEE Trans. Auton. Ment. Dev., 2011)

NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals. - Nikola K. Kasabov (ANNPR, 2012)

Constructing Robust Liquid State Machines to Process Highly Variable Data Streams. - Stefan Schliebs; Maurizio Fiasché; Nikola K. Kasabov (ICANN (1), 2012)

Evaluating SPAN Incremental Learning for Handwritten Digit Recognition. - Ammar Mohemmed; Guoyu Lu; Nikola K. Kasabov (ICONIP (3), 2012)

Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning. - Kshitij Dhoble; Nuttapod Nuntalid; Giacomo Indiveri; Nikola K. Kasabov (IJCNN, 2012)

Incremental learning algorithm for spatio-temporal spike pattern classification. - Ammar Mohemmed; Nikola K. Kasabov (IJCNN, 2012)

Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition. - Nikola K. Kasabov (IEEE Conf. of Intelligent Systems, 2012)

Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition. - Nikola K. Kasabov (WCCI, 2012)

Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns. - Ammar Mohemmed; Stefan Schliebs; Satoshi Matsuda; Nikola K. Kasabov (Int. J. Neural Syst., 2012)

LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration. - Shaoning Pang 001; Tao Ban; Youki Kadobayashi; Nikola K. Kasabov (IEEE Trans. Syst. Man Cybern. Part B, 2012)

The Evolution of the Evolving Neuro-Fuzzy Systems: From Expert Systems to Spiking-, Neurogenetic-, and Quantum Inspired. - Nikola K. Kasabov (On Fuzziness (1), 2013)

Towards a Wearable Coach: Classifying Sports Activities with Reservoir Computing. - Stefan Schliebs; Nikola K. Kasabov; Dave Parry; Doug Hunt (EANN (1), 2013)

NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks. - Yixiong Chen; Jin Hu; Nikola K. Kasabov; Zeng-Guang Hou; Long Cheng 001 (ICONIP (3), 2013)

Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples. - Nikola K. Kasabov; Jin Hu; Yixiong Chen; Nathan Matthew Scott; Yulia Turkova (ICONIP (3), 2013)

Spiking Neural Network for On-line Cognitive Activity Classification Based on EEG Data. - Stefan Schliebs; Elisa Capecci; Nikola K. Kasabov (ICONIP (3), 2013)

NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation. - Nathan Matthew Scott; Nikola K. Kasabov; Giacomo Indiveri (ICONIP (3), 2013)

Salient Object Segmentation Based on Automatic Labeling. - Lei Zhou 003; Chen Gong 002; Yijun Li 003; Yu Qiao 001; Jie Yang 002; Nikola K. Kasabov (ICONIP (3), 2013)

Evolving integrated multi-model framework for on line multiple time series prediction. - Russel Pears; Harya Widiputra; Nikola K. Kasabov (Evol. Syst., 2013)

Evolving spiking neural network - a survey. - Stefan Schliebs; Nikola K. Kasabov (Evol. Syst., 2013)

Training spiking neural networks to associate spatio-temporal input-output spike patterns. - Ammar Mohemmed; Stefan Schliebs; Satoshi Matsuda; Nikola K. Kasabov (Neurocomputing, 2013)

Special Issue: Contemporary development of neural computation and applications. - Ivan Jordanov; Bruno Apolloni; Nikola K. Kasabov (Neural Comput. Appl., 2013)

EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation. - Jin Hu; Zeng-Guang Hou; Yixiong Chen; Nikola K. Kasabov; Nathan Matthew Scott (BioRob, 2014)

Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model. - Maryam Gholami Doborjeh; Elisa Capecci; Nikola K. Kasabov (EALS, 2014)

Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture. - Norhanifah Murli; Nikola K. Kasabov; Bana Handaga (ICONIP (1), 2014)

Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework. - Enmei Tu; Jie Yang 002; Zhenghong Jia; Nikola K. Kasabov (ICONIP (1), 2014)

Unsupervised Segmentation Using Cluster Ensembles. - Wei Zhang; Jie Yang 002; Wenjing Jia; Nikola K. Kasabov; Zhenhong Jia; Lei Zhou 003 (ICONIP (3), 2014)

Extracting temporal knowledge from time series: A case study in ecological data. - Reggio N. Hartono; Russel Pears; Nikola K. Kasabov; Susan P. Worner (IJCNN, 2014)

Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data. - Muhaini Othman; Nikola K. Kasabov; Enmei Tu; Valery Feigin; Rita Krishnamurthi; Zheng-Guang Hou; Yixiong Chen; Jin Hu (IJCNN, 2014)

Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications. - Denise Taylor; Nathan Matthew Scott; Nikola K. Kasabov; Elisa Capecci; Enmei Tu; Nicola Saywell; Yixiong Chen; Jin Hu; Zeng-Guang Hou (IJCNN, 2014)

NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data. - Enmei Tu; Nikola K. Kasabov; Muhaini Othman; Yuxiao Li; Susan P. Worner; Jie Yang 002; Zhenghong Jia (IJCNN, 2014)

An enhanced multiphase Chan-Vese model for the remote sensing image segmentation. - Xin Yi; Yingjie Hu; Zhenhong Jia; Liejun Wang; Jie Yang 002; Nikola K. Kasabov (Concurr. Comput. Pract. Exp., 2014)

Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke. - Nikola K. Kasabov; Valery Feigin; Zeng-Guang Hou; Yixiong Chen; Linda Liang; Rita Krishnamurthi; Muhaini Othman; Priya Parmar (Neurocomputing, 2014)

A novel graph-based k-means for nonlinear manifold clustering and representative selection. - Enmei Tu; Longbing Cao; Jie Yang 002; Nikola K. Kasabov (Neurocomputing, 2014)

NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. - Nikola K. Kasabov (Neural Networks, 2014)

Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data. - Maryam Gholami Doborjeh; Nikola K. Kasabov (ICONIP (4), 2015)

Adaptive Location for Multiple Salient Objects Detection. - Shaoyong Jia; Yuding Liang; Xianyang Chen; Yun Gu; Jie Yang 002; Nikola K. Kasabov; Yu Qiao 003 (ICONIP (3), 2015)

Poisson Image Denoising Based on BLS-GSM Method. - Liangdong Li; Nikola K. Kasabov; Jie Yang 002; Lixiu Yao; Zhenghong Jia (ICONIP (4), 2015)

Abnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation. - Yu Zhao 034; Yu Qiao 003; Jie Yang 002; Nikola K. Kasabov (ICONIP (4), 2015)

Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture. - Elisa Capecci; Josafath Israel Espinosa Ramos; Nadia Mammone; Nikola K. Kasabov; Jonas Duun-Henriksen; Troels Wesenberg Kjaer; Maurizio Campolo; Fabio La Foresta; Francesco Carlo Morabito (IJCNN, 2015)

sEMG-based torque estimation for robot-assisted lower limb rehabilitation. - Long Peng 001; Zeng-Guang Hou; Nikola K. Kasabov; Jin Hu; Liang Peng; Weiqun Wang (IJCNN, 2015)

Identifying overlapping mutated driver pathways by constructing gene networks in cancer. - Hao Wu 062; Lin Gao 006; Feng Li 033; Fei Song; Xiaofei Yang 003; Nikola K. Kasabov (BMC Bioinform., 2015)

Evolving personalized modeling system for integrated feature, neighborhood and parameter optimization utilizing gravitational search algorithm. - Wen Liang; Yingjie Hu; Nikola K. Kasabov (Evol. Syst., 2015)

Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance. - Enmei Tu; Jie Yang 002; Nikola K. Kasabov; Yaqian Zhang 004 (Neurocomputing, 2015)

A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking. - Lu Liu; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Int. J. Imaging Syst. Technol., 2015)

Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast. - Jing-jing Wang; Zhenhong Jia; Xizhong Qin; Jie Yang 002; Nikola K. Kasabov (Int. J. Imaging Syst. Technol., 2015)

Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes. - Nikola K. Kasabov; Elisa Capecci (Inf. Sci., 2015)

A method used for Dotted Data Matrix image processing. - Tao Gao; Nikola K. Kasabov (J. Comput. Methods Sci. Eng., 2015)

Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions. - Nikola K. Kasabov (Knowl. Based Syst., 2015)

Analysis of connectivity in NeuCube spiking neural network models trained on EEG data for the understanding of functional changes in the brain: A case study on opiate dependence treatment. - Elisa Capecci; Nikola K. Kasabov; Grace Y. Wang (Neural Networks, 2015)

Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic. - Nikola K. Kasabov (Handbook of Computational Intelligence, 2015)

A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer's Disease EEG Data. - Elisa Capecci; Francesco Carlo Morabito; Maurizio Campolo; Nadia Mammone; Domenico Labate; Nikola K. Kasabov (Advances in Neural Networks, 2015)

A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG). - Vivienne Breen; Nikola K. Kasabov; Peng Du; Stefan Calder (ANNPR, 2016)

Cyber fraud detection using evolving spiking neural network. - Amit Soni Arya; Vadlamani Ravi; Vadali Tejasviram; Neelava Sengupta; Nikola K. Kasabov (ICIIS, 2016)

Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine. - Zohreh Gholami Doborjeh; Maryam Gholami Doborjeh; Nikola K. Kasabov (ICONIP (4), 2016)

Analysis of Similarity and Differences in Brain Activities Between Perception and Production of Facial Expressions Using EEG Data and the NeuCube Spiking Neural Network Architecture. - Hideaki Kawano; Akinori Seo; Zohreh Gholami Doborjeh; Nikola K. Kasabov; Maryam Gholami Doborjeh (ICONIP (4), 2016)

Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture. - Anne Abbott; Neelava Sengupta; Nikola K. Kasabov (IJCNN, 2016)

Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model. - Elisa Capecci; Zohreh Gholami Doborjeh; Nadia Mammone; Fabio La Foresta; Francesco Carlo Morabito; Nikola K. Kasabov (IJCNN, 2016)

Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system. - Maryam Gholami Doborjeh; Nikola K. Kasabov (IJCNN, 2016)

From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine. - Nikola K. Kasabov; Neelava Sengupta; Nathan Matthew Scott (IEEE Conf. on Intelligent Systems, 2016)

Mapping Temporal Variables into the NeuCube for Improved Pattern Recognition, Predictive Modelling and Understanding of Stream Data. - Enmei Tu; Nikola K. Kasabov; Jie Yang 002 (CoRR, 2016)

Adaptive cow movement detection using evolving spiking neural network models. - Tao Gao; Nikola K. Kasabov (Evol. Syst., 2016)

An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition. - Yu Cheng; Zhigang Jin; Tao Gao; Hongcai Chen; Nikola K. Kasabov (Neurocomputing, 2016)

A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification. - Enmei Tu; Yaqian Zhang 004; Lin Zhu; Jie Yang 002; Nikola K. Kasabov (Inf. Sci., 2016)

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications. - Nikola K. Kasabov; Nathan Matthew Scott; Enmei Tu; Stefan Marks; Neelava Sengupta; Elisa Capecci; Muhaini Othman; Maryam Gholami Doborjeh; Norhanifah Murli; Reggio N. Hartono; Josafath Israel Espinosa Ramos; Lei Zhou 003; et al. (Neural Networks, 2016)

A Spiking Neural Network Methodology and System for Learning and Comparative Analysis of EEG Data From Healthy Versus Addiction Treated Versus Addiction Not Treated Subjects. - Maryam Gholami Doborjeh; Grace Y. Wang; Nikola K. Kasabov; Robert Kydd; Bruce Russell (IEEE Trans. Biomed. Eng., 2016)

Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data. - Hao Wu 062; Lin Gao 006; Nikola K. Kasabov (IEEE ACM Trans. Comput. Biol. Bioinform., 2016)

Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series. - Pritam Bose; Nikola K. Kasabov; Lorenzo Bruzzone; Reggio N. Hartono (IEEE Trans. Geosci. Remote. Sens., 2016)

Robust Kernel Approximation for Classification. - Fanghui Liu 001; Xiaolin Huang; Cheng Peng 004; Jie Yang 002; Nikola K. Kasabov (ICONIP (1), 2017)

EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube. - Yuma Omori; Hideaki Kawano; Akinori Seo; Zohreh Gholami Doborjeh; Nikola K. Kasabov; Maryam Gholami Doborjeh (ICONIP (4), 2017)

Correlation Filters with Adaptive Memories and Fusion for Visual Tracking. - Cheng Peng 004; Fanghui Liu 001; Haiyan Yang; Jie Yang 002; Nikola K. Kasabov (ICONIP (3), 2017)

A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering. - Dayong Ren; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2017)

A spiking neural network model for obstacle avoidance in simulated prosthetic vision. - Chenjie Ge; Nikola K. Kasabov; Zhi Liu 003; Jie Yang 002 (Inf. Sci., 2017)

Spike-time encoding as a data compression technique for pattern recognition of temporal data. - Neelava Sengupta; Nikola K. Kasabov (Inf. Sci., 2017)

基于众包的嵌套流形匹配室内定位方法 (Crowdsourcing-based Indoor Localization via Embedded Manifold Matching). - Apeng Zhou; Xizhong Qin; Zhenhong Jia; Nikola K. Kasabov (计算机科学, 2017)

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application. - Pengyun Chen; Yichen Zhang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2017)

Image Processing of Porous Silicon Microarray in Refractive Index Change Detection. - Zhiqing Guo; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov; Chuanxi Li (Sensors, 2017)

New Algorithms for Encoding, Learning and Classification of fMRI Data in a Spiking Neural Network Architecture: A Case on Modeling and Understanding of Dynamic Cognitive Processes. - Nikola K. Kasabov; Lei Zhou 003; Maryam Gholami Doborjeh; Zohreh Gholami Doborjeh; Jie Yang 002 (IEEE Trans. Cogn. Dev. Syst., 2017)

Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks. - Nikola K. Kasabov; Maryam Gholami Doborjeh; Zohreh Gholami Doborjeh (IEEE Trans. Neural Networks Learn. Syst., 2017)

Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data. - Enmei Tu; Nikola K. Kasabov; Jie Yang 002 (IEEE Trans. Neural Networks Learn. Syst., 2017)

Deep Learning in Spiking Neural Networks for Brain-Inspired Artificial Intelligence. - Nikola K. Kasabov (CompSysTech, 2018)

A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI. - Mingjian Chen; Hao Zheng 008; Changsheng Lu; Enmei Tu; Jie Yang 002; Nikola K. Kasabov (ICONIP (7), 2018)

Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis. - Jack Dray; Elisa Capecci; Nikola K. Kasabov (ICONIP (1), 2018)

Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks. - Durgesh Nandini; Elisa Capecci; Lucien Koefoed; Ibai Laña; Gautam Kishore Shahi; Nikola K. Kasabov (ICONIP (1), 2018)

Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks. - Gautam Kishore Shahi; Imanol Bilbao; Elisa Capecci; Durgesh Nandini; Maria Choukri; Nikola K. Kasabov (ICONIP (5), 2018)

Discrete Sparse Hashing for Cross-Modal Similarity Search. - Lu Wang 048; Chao Ma 005; Enmei Tu; Jie Yang 002; Nikola K. Kasabov (ICONIP (4), 2018)

FaNeuRobot: A Framework for Robot and Prosthetics Control Using the NeuCube Spiking Neural Network Architecture and Finite Automata Theory. - Kaushalya Kumarasinghe; Mahonri Owen; Denise Taylor; Nikola K. Kasabov; Chi Kit (ICRA, 2018)

Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks. - Ibai Laña; Elisa Capecci; Javier Del Ser; Jesus L. Lobo; Nikola K. Kasabov (IDC, 2018)

Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks. - Jesus L. Lobo; Javier Del Ser; Ibai Laña; Miren Nekane Bilbao; Nikola K. Kasabov (IDC, 2018)

EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes. - Zohreh Gholami Doborjeh; Maryam Gholami Doborjeh; Nikola K. Kasabov (IJCNN, 2018)

Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection. - Lucien Koefoed; Elisa Capecci; Nikola K. Kasabov (IJCNN, 2018)

Speckle Reduction of Reconstructions of Digital Holograms Using Gamma-Correction and Filtering. - Xiaohui Huang 005; Zhenhong Jia; Junlin Zhou; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2018)

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework. - Obada Al Zoubi; Mariette Awad; Nikola K. Kasabov (Artif. Intell. Medicine, 2018)

Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data. - Zohreh Gholami Doborjeh; Maryam Gholami Doborjeh; Nikola K. Kasabov (Cogn. Comput., 2018)

An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks. - Fahad Bashir Alvi; Russel Pears; Nikola K. Kasabov (Evol. Syst., 2018)

Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data. - Maryam Gholami Doborjeh; Nikola K. Kasabov; Zohreh Gholami Doborjeh (Evol. Syst., 2018)

A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors. - Lukas Paulun; Anne Wendt; Nikola K. Kasabov (Frontiers Comput. Neurosci., 2018)

Evolving Spiking Neural Networks for online learning over drifting data streams. - Jesus L. Lobo; Ibai Laña; Javier Del Ser; Miren Nekane Bilbao; Nikola K. Kasabov (Neural Networks, 2018)

Densely Connected Discriminative Correlation Filters for Visual Tracking. - Cheng Peng 004; Fanghui Liu 001; Jie Yang 002; Nikola K. Kasabov (IEEE Signal Process. Lett., 2018)

Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters. - Cheng Peng 004; Fanghui Liu 001; Jie Yang 002; Nikola K. Kasabov (IEEE Signal Process. Lett., 2018)

Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modeling. - Neelava Sengupta; Carolyn B. McNabb; Nikola K. Kasabov; Bruce Russell (IEEE Trans. Neural Networks Learn. Syst., 2018)

Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression. - Dhvani Shah; Grace Y. Wang; Maryam Doborjeh; Zohreh Gholami Doborjeh; Nikola K. Kasabov (ICONIP (3), 2019)

eSPANNet: Evolving Spike Pattern Association Neural Network for Spike-based Supervised Incremental Learning and Its Application for Single-trial Brain Computer Interfaces. - Kaushalya Kumarasinghe; Denise Taylor; Nikola K. Kasabov (IJCNN, 2019)

SAR Image Change Detection Based on Mathematical Morphology and the K-Means Clustering Algorithm. - Luyang Liu; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2019)

Multi-Spectral Image Change Detection Based on Band Selection and Single-Band Iterative Weighting. - Liyuan Ma; Zhenhong Jia; Yinfeng Yu; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2019)

Quasi-Noise-Free and Detail-Preserved Digital Holographic Reconstruction. - Ruyong Ren; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov; Xiaohui Huang 005 (IEEE Access, 2019)

Moving Target Detection Based on Improved Gaussian Mixture Background Subtraction in Video Images. - Junhui Zuo; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2019)

Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area. - Piotr S. Maciag; Nikola K. Kasabov; Marzena Kryszkiewicz; Robert Bembenik (Environ. Model. Softw., 2019)

Contrast enhancement of medical images using fuzzy set theory and nonsubsampled shearlet transform. - Guo Qingrong; Jia Zhenhong; Yang Jie; Nikola K. Kasabov (Int. J. Imaging Syst. Technol., 2019)

A Practical Medical Image Enhancement Algorithm Based on Nonsubsampled Contourlet Transform. - Liangliang Li 001; Linli Wang; Zhenhong Jia; Yujuan Si; Jie Yang 002; Nikola K. Kasabov (J. Medical Imaging Health Informatics, 2019)

A Novel Medical Image Fusion Approach Based on Nonsubsampled Shearlet Transform. - Liangliang Li 001; Linli Wang; Zuoxu Wang; Zhenhong Jia; Yujuan Si; Jie Yang 002; Nikola K. Kasabov (J. Medical Imaging Health Informatics, 2019)

Personalised modelling with spiking neural networks integrating temporal and static information. - Maryam Doborjeh; Nikola K. Kasabov; Zohreh Gholami Doborjeh; Reza Enayatollahi; Enmei Tu; Amir H. Gandomi (Neural Networks, 2019)

Spiking neural networks for deep learning and knowledge representation: Editorial. - Nikola K. Kasabov (Neural Networks, 2019)

Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method. - Xuemei Lou; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2019)

Erratum: Lou, X.; Jia, Z.; Yang, J.; Kasabov, N. Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method. Sensors 2019, 19, 1179. - Xuemei Lou; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2019)

Applying Speckle Noise Suppression to Refractive Indices Change Detection in Porous Silicon Microarrays. - Ruyong Ren; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2019)

Change Detection of Optical Remote Sensing Image Disturbed by Thin Cloud Using Wavelet Coefficient Substitution Algorithm. - Xiaoqian Yang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2019)

A Computational Model of Neuroreceptor-Dependent Plasticity (NRDP) Based on Spiking Neural Networks. - Josafath Israel Espinosa Ramos; Elisa Capecci; Nikola K. Kasabov (IEEE Trans. Cogn. Dev. Syst., 2019)

Application of an Improved Focal Loss in Vehicle Detection. - Xuanlin He; Jie Yang 002; Nikola K. Kasabov (ICAISC (1), 2020)

Sleep Stage Classification using NeuCube on SpiNNaker: a Preliminary Study. - Sugam Budhraja; Basabdatta Sen Bhattacharya; Simon Durrant; Zohreh Gholami Doborjeh; Maryam Gholami Doborjeh; Nikola K. Kasabov (IJCNN, 2020)

Universal Adversarial Perturbation Generated by Attacking Layer-wise Relevance Propagation. - Zifei Wang; Xiaolin Huang; Jie Yang 002; Nikola K. Kasabov (IEEE Conf. on Intelligent Systems, 2020)

Vehicle-Related Scene Segmentation Using CapsNets. - Xiaoxu Liu; Wei Qi Yan 001; Nikola K. Kasabov (IVCNZ, 2020)

eSNN for Spatio-Temporal fMRI Brain Pattern Recognition with a Graphical Object Recognition Case Study. - Norhanifah Murli; Nikola K. Kasabov; Nurul Amirah Paham (SCDM, 2020)

Blue Channel and Fusion for Sandstorm Image Enhancement. - Yaqiao Cheng; Zhenhong Jia; Huicheng Lai; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

A Fast Sand-Dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering. - Yaqiao Cheng; Zhenhong Jia; Huicheng Lai; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

A Multi-Information Fusion Correlation Filters Tracker. - Junnan Wang; Zhenhong Jia; Huicheng Lai; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

Video Snow Removal Based on Self-Adaptation Snow Detection and Patch-Based Gaussian Mixture Model. - Bin Yang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

Object Motion Deblurring in Single Image Under Static Background. - Tengteng Zhang; Sensen Song; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

Change Detection in Multitemporal Monitoring Images Under Low Illumination. - Yong Zhu; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2020)

A Dynamic DNA Color Image Encryption Method Based on SHA-512. - Shihua Zhou; Pinyan He; Nikola K. Kasabov (Entropy, 2020)

Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks. - Elisa Capecci; Jesus L. Lobo; Ibai Laña; Josafath Israel Espinosa Ramos; Nikola K. Kasabov (Evol. Syst., 2020)

Deep learning neural networks: Methods, systems, and applications. - Qinglai Wei; Nikola K. Kasabov; Marios M. Polycarpou; Zhigang Zeng (Neurocomputing, 2020)

An efficient and high quality medical CT image enhancement algorithm. - Zhi Li 077; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Int. J. Imaging Syst. Technol., 2020)

Remote sensing image enhancement based on the combination of adaptive nonlinear gain and the PLIP model in the NSST domain. - Lanhua Zhang; Zhenhong Jia; Lucien Koefoed; Jie Yang 002; Nikola K. Kasabov (Multim. Tools Appl., 2020)

Moving object detection in video sequence images based on an improved visual background extraction algorithm. - Junhui Zuo; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Multim. Tools Appl., 2020)

Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces. - Kaushalya Kumarasinghe; Nikola K. Kasabov; Denise Taylor (Neural Networks, 2020)

Spiking Neural Networks and online learning: An overview and perspectives. - Jesus L. Lobo; Javier Del Ser; Albert Bifet; Nikola K. Kasabov (Neural Networks, 2020)

Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture. - Clarence Tan; Marko Sarlija; Nikola K. Kasabov (Neural Process. Lett., 2020)

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture. - Zohreh Gholami Doborjeh; Maryam Doborjeh; Mark Crook-Rumsey; Tamasin Taylor; Grace Y. Wang; David Moreau; Christian U. Krägeloh; Wendy Wrapson; Richard J. Siegert; Nikola K. Kasabov; Grant Searchfield; Alexander Sumich (Sensors, 2020)

FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network. - Clarence Tan; Gerardo Ceballos; Nikola K. Kasabov; Narayan Puthanmadam Subramaniyam (Sensors, 2020)

Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification. - Anup Vanarse; Josafath Israel Espinosa Ramos; Adam Osseiran; Alexander Rassau; Nikola K. Kasabov (Sensors, 2020)

Pulsewidth Modulation-Based Algorithm for Spike Phase Encoding and Decoding of Time-Dependent Analog Data. - Ander Arriandiaga; Eva Portillo; Josafath Israel Espinosa Ramos; Nikola K. Kasabov (IEEE Trans. Neural Networks Learn. Syst., 2020)

Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks. - Balint Petro; Nikola K. Kasabov; Rita M. Kiss (IEEE Trans. Neural Networks Learn. Syst., 2020)

Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture. - Wael Alzhrani; Maryam Doborjeh; Zohreh Gholami Doborjeh; Nikola K. Kasabov (IJCNN, 2021)

Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives. - Yawen Lu; Nikola K. Kasabov; Guoyu Lu (IJCNN, 2021)

An Effective Algorithm for Specular Reflection Image Enhancement. - Zhuang Huang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2021)

Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network. - Aiwen Jia; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Access, 2021)

Spiking Neural Networks for Computational Intelligence: An Overview. - Shirin Dora; Nikola K. Kasabov (Big Data Cogn. Comput., 2021)

A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners. - Urtats Etxegarai; Eva Portillo; Jon Irazusta; Lucien Koefoed; Nikola K. Kasabov (Eur. J. Oper. Res., 2021)

NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns. - Clarence Tan; Marko Sarlija; Nikola K. Kasabov (Neurocomputing, 2021)

Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia. - Maryam Doborjeh; Zohreh Gholami Doborjeh; Alexander Merkin; Helena Bahrami; Alexander Sumich; Rita Krishnamurthi; Oleg N. Medvedev; Mark Crook-Rumsey; Catherine Morgan; Ian J. Kirk; Perminder S. Sachdev; Henry Brodaty; et al. (Neural Networks, 2021)

Multispectral Image Change Detection Based on Single-Band Slow Feature Analysis. - Youxi He; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Remote. Sens., 2021)

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network. - Maryam Doborjeh; Zohreh Gholami Doborjeh; Nikola K. Kasabov; Molood Barati; Grace Y. Wang (Sensors, 2021)

Video Desnowing and Deraining via Saliency and Dual Adaptive Spatiotemporal Filtering. - Yongji Li; Rui Wu; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2021)

Universal Adversarial Perturbation Generated by Using Attention Information. - Zifei Wang; Xiaolin Huang; Jie Yang 002; Nikola K. Kasabov (Advances in Intelligent Systems Research and Innovation, 2022)

Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives. - Devarth Parikh; Yawen Lu; Nikola K. Kasabov; Guoyu Lu (IJCNN, 2022)

Why Use Evolving Neuro-Fuzzy and Spiking Neural Networks for incremental and explainable learning of time series? A case study on predictive modelling of trade imports and outlier detection. - Iman Abouhassan; Nikola K. Kasabov; George Popov; Roumen Trifonov (IS, 2022)

Machine learning methods for the study of cybersickness: a systematic review. - Alexander Hui Xiang Yang; Nikola K. Kasabov; Yusuf Özgür Çakmak (Brain Informatics, 2022)

Personalized Spiking Neural Network Models of Clinical and Environmental Factors to Predict Stroke. - Maryam Doborjeh; Zohreh Gholami Doborjeh; Alexander Merkin; Rita Krishnamurthi; Reza Enayatollahi; Valery Feigin; Nikola K. Kasabov (Cogn. Comput., 2022)

A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks. - Aitor Martínez-Seras; Javier Del Ser; Jesus L. Lobo; Pablo García Bringas; Nikola K. Kasabov (CoRR, 2022)

A meta-inspired termite queen algorithm for global optimization and engineering design problems. - Peng Chen; Shihua Zhou; Qiang Zhang 008; Nikola K. Kasabov (Eng. Appl. Artif. Intell., 2022)

Salient detection via the fusion of background-based and multiscale frequency-domain features. - Sensen Song; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Inf. Sci., 2022)

A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy. - Dongdong Ni; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (J. Real Time Image Process., 2022)

Multispectral Image Enhancement Based on Weighted Principal Component Analysis and Improved Fractional Differential Mask. - Weijie Chen; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Geosci. Remote. Sens. Lett., 2022)

Deep semi-supervised learning via dynamic anchor graph embedding in latent space. - Enmei Tu; Zihao Wang; Jie Yang 002; Nikola K. Kasabov (Neural Networks, 2022)

Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model. - Weijie Chen; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Remote. Sens., 2022)

Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior. - Lingli Guo; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2022)

Denoising of Fluorescence Image on the Surface of Quantum Dot/Nanoporous Silicon Biosensors. - Yong Liu; Miao Sun; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Sensors, 2022)

Mosaic LSM: A Liquid State Machine Approach for Multimodal Longitudinal Data Analysis. - Sugam Budhraja; Balkaran Singh; Maryam Doborjeh; Zohreh Gholami Doborjeh; Samuel Tan; Edmund M.-K. Lai; Wilson Wen Bin Goh; Nikola K. Kasabov (IJCNN, 2023)

On-line Learning, Classification and Interpretation of Brain Signals using 3D SNN and ESN. - Petia D. Koprinkova-Hristova; Dimitar P. Filev; Simona Nedelcheva; Svetlozar Yordanov; Nikola K. Kasabov (IJCNN, 2023)

Grid Search Optimization of Novel SNN-ESN Classifier on a Supercomputer Platform. - Dimitar P. Filev; Petia D. Koprinkova-Hristova; Nikola K. Kasabov; Simona Nedelcheva; Sofiya Ivanovska; Svetlozar Yordanov (LSSC, 2023)

Neuroinformatics, Neural Networks and Neurocomputers for Brain-inspired Computational Intelligence. - Nikola K. Kasabov (SACI, 2023)

Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment. - Mark Crook-Rumsey; Christina J. Howard; Zohreh Gholami Doborjeh; Maryam Doborjeh; Josafath Israel Espinosa Ramos; Nikola K. Kasabov; Alexander Sumich (Cogn. Comput., 2023)

Integrating Spatial and Temporal Information for Violent Activity Detection from Video Using Deep Spiking Neural Networks. - Xiang Wang; Jie Yang 002; Nikola K. Kasabov (Sensors, 2023)

Image Segmentation Based on Fuzzy Low-Rank Structural Clustering. - Sensen Song; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Trans. Fuzzy Syst., 2023)

GALFusion: Multi-Exposure Image Fusion via a Global-Local Aggregation Learning Network. - Jia Lei; Jiawei Li 016; Jinyuan Liu 001; Shihua Zhou; Qiang Zhang 008; Nikola K. Kasabov (IEEE Trans. Instrum. Meas., 2023)

Sand-dust image enhancement based on light attenuation and transmission compensation. - Fei Shi; Zhenhong Jia; Huicheng Lai; Nikola K. Kasabov; Sensen Song; Junnan Wang (Multim. Tools Appl., 2023)

Learning a Coordinated Network for Detail-Refinement Multiexposure Image Fusion. - Jiawei Li 016; Jinyuan Liu 001; Shihua Zhou; Qiang Zhang 008; Nikola K. Kasabov (IEEE Trans. Circuits Syst. Video Technol., 2023)

A fast and effective algorithm for specular reflection image enhancement. - Ye Xin; Yifei Wei; Zhuang Huang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Multim. Tools Appl., 2023)

A dual channel decomposition and remapping fusion model for low illumination images with a wide field of view. - Wei Zhang; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Signal Process. Image Commun., 2023)

Unsupervised Change Detection in Wide-Field Video Images Under Low Illumination. - Baoqiang Shi; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Trans. Circuits Syst. Video Technol., 2023)

Filter and Wrapper Stacking Ensemble (FWSE): a robust approach for reliable biomarker discovery in high-dimensional omics data. - Sugam Budhraja; Maryam Doborjeh; Balkaran Singh; Samuel Tan; Zohreh Gholami Doborjeh; Edmund M.-K. Lai; Alexander Merkin; Jimmy Lee; Wilson Wen Bin Goh; Nikola K. Kasabov (Briefings Bioinform., 2023)

A fast sand-dust video quality improvement method using simple color balance and dynamic guided filtering. - Dongdong Ni; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Multim. Tools Appl., 2023)

Obituary Edwin Lughofer (1972-2023). - Plamen Angelov 001; Dimitar P. Filev; Nikola K. Kasabov; Daniel Leite 001; Maharadhika Pratama; Susanne Saminger-Platz; Erich-Peter Klement (Evol. Syst., 2023)

A real-time quality improvement method based on an adaptive dynamic screened Poisson equation for surveillance video in sand-dust weather. - Dongdong Ni; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (J. Real Time Image Process., 2023)

Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability. - Alexander Hui Xiang Yang; Nikola K. Kasabov; Yusuf Özgür Çakmak (Brain Informatics, 2023)

Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks. - Piotr S. Maciag; Robert Bembenik; Aleksandra Piekarzewicz; Javier Del Ser; Jesus L. Lobo; Nikola K. Kasabov (Environ. Model. Softw., 2023)

A novel Out-of-Distribution detection approach for Spiking Neural Networks: Design, fusion, performance evaluation and explainability. - Aitor Martínez-Seras; Javier Del Ser; Jesus L. Lobo; Pablo García Bringas; Nikola K. Kasabov (Inf. Fusion, 2023)

Accurate breast lesion segmentation by exploiting spatio-temporal information with deep recurrent and convolutional network. - Mingjian Chen; Hao Zheng 008; Changsheng Lu; Enmei Tu; Jie Yang 002; Nikola K. Kasabov (J. Ambient Intell. Humaniz. Comput., 2023)

Transfer Learning of Fuzzy Spatio-Temporal Rules in a Brain-Inspired Spiking Neural Network Architecture: A Case Study on Spatio-Temporal Brain Data. - Nikola K. Kasabov; Yongyao Tan; Maryam Doborjeh; Enmei Tu; Jie Yang 002; Wilson Wen Bin Goh; Jimmy Lee (IEEE Trans. Fuzzy Syst., 2023)

Predictive and Explainable Modelling in Economics on the Case Study of Remittance Prediction Using the NeuDen AI Computational Architecture. - Iman Abouhassan; Nikola K. Kasabov; Roumen Trifonov; George Popov (AIMSA, 2024)

Neurocomputational Modelling of EEG Connectivity: Links Between Depression, Inflammation, and Gut-Microbiome. - Zohreh Doborjeh; Daniel lavin; Kirsty Hunter; Nadja Heym; Bryony Heasman; Maryam Doborjeh; Nikola K. Kasabov; Glen Gibson; Alexander Sumich (BI (1), 2024)

Izhikevich Neurons in NeuCube for Longitudinal Data Classification. - Balkaran Singh; Sugam Budhraja; Maryam Doborjeh; Zohreh Doborjeh; Edmund M.-K. Lai; Nikola K. Kasabov (ICONIP (11), 2024)

Calming the Mind: Spiking Neural Networks Reveal How Havening Touch to Reduce Persistent Distress Attenuates Left Temporal Electroencephalographic Connectivity. - Alexander Sumich; Zohreh Doborjeh; Nadja Heym; Aroha Scott; Kirsty Hunter; Tony Burgess; Julie French; Mustafa Sarkar; Maryam Doborjeh; Nikola K. Kasabov (ICONIP (11), 2024)

Depth prior-based stable tensor decomposition for video snow removal. - Yongji Li; Luping Wang 002; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (Displays, 2024)

SDFuse: Semantic-injected dual-flow learning for infrared and visible image fusion. - Enlong Wang; Jiawei Li 016; Jia Lei; Jinyuan Liu 001; Shihua Zhou; Bin Wang 005; Nikola K. Kasabov (Expert Syst. Appl., 2024)

Constructing New Backbone Networks via Space-Frequency Interactive Convolution for Deepfake Detection. - Zhiqing Guo; Zhenhong Jia; Liejun Wang; Dewang Wang; Gaobo Yang; Nikola K. Kasabov (IEEE Trans. Inf. Forensics Secur., 2024)

Online Low-Light Sand-Dust Video Enhancement Using Adaptive Dynamic Brightness Correction and a Rolling Guidance Filter. - Dongdong Ni; Zhenhong Jia; Jie Yang 002; Nikola K. Kasabov (IEEE Trans. Multim., 2024)

Saliency optimization fused background feature with frequency domain features. - Sensen Song; Zhenhong Jia; Fei Shi; Junnan Wang; Jie Yang 002; Nikola K. Kasabov (Multim. Tools Appl., 2024)

Moving vehicle tracking and scene understanding: A hybrid approach. - Xiaoxu Liu; Wei Qi Yan 001; Nikola K. Kasabov (Multim. Tools Appl., 2024)

Multiscale Bilateral Attention Fusion Network for Pansharpening. - Zhongyuan Guo; Jiawei Li 016; Jia Lei; Jinyuan Liu 001; Shihua Zhou; Bin Wang 005; Nikola K. Kasabov (IEEE Trans. Artif. Intell., 2024)

GeSeNet: A General Semantic-Guided Network With Couple Mask Ensemble for Medical Image Fusion. - Jiawei Li 016; Jinyuan Liu 001; Shihua Zhou; Qiang Zhang 008; Nikola K. Kasabov (IEEE Trans. Neural Networks Learn. Syst., 2024)

A multispectral pansharpening method based on CNN-DI network with mixture of experts. - Zhongyuan Guo; Jia Lei; Shihua Zhou; Bin Wang 005; Nikola K. Kasabov (Appl. Soft Comput., 2025)

MLFuse: Multi-Scenario Feature Joint Learning for Multi-Modality Image Fusion. - Jia Lei; Jiawei Li 016; Jinyuan Liu 001; Bin Wang 005; Shihua Zhou; Qiang Zhang 008; Xiaopeng Wei; Nikola K. Kasabov (IEEE Trans. Multim., 2025)

ePAMeT: evolving predictive associative memories for time series. - Iman Abouhassan; Nikola K. Kasabov; Tanmay Bankar; Rishabh Garg; Basabdatta Sen Bhattacharya (Evol. Syst., 2025)

NeuDen: a framework for the integration of neuromorphic evolving spiking neural networks with dynamic evolving neuro-fuzzy systems for predictive and explainable modelling of streaming data. - Iman Yakzan Abou Hassan; Nikola K. Kasabov (Evol. Syst., 2025)

New Eigenvalue-Based Analysis for Precise Limit Cycle Stability Assessment in a Two-State Epileptor Model. - Samaneh-Alsadat Saeedinia; Mohammad Reza Jahed-Motlagh; Nikola K. Kasabov; Abbas Tafakhori (IEEE Trans. Syst. Man Cybern. Syst., 2025)

Machine learning-guided high-definition transcranial direct current stimulation prevents cybersickness. - Alexander Hui Xiang Yang; Cristian Galán-Augé; Nikola Kirilov Kasabov; Yusuf Özgür Çakmak (Virtual Real., 2025)