Nikola K. Kasabov

发表

A versatile quantum-inspired evolutionary algorithm

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2007, 2007 IEEE Congress on Evolutionary Computation.

Fast Estimation of Distribution Algorithm (EDA) via Constrained Multi-Parent Recombination

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, SGAI Conf..

Blue Channel and Fusion for Sandstorm Image Enhancement

Nikola K. Kasabov, Yaqiao Cheng, Zhenhong Jia, 2020, IEEE Access.

Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications

Maryam Gholami Doborjeh, Muhaini Othman, Jie Yang, 2016, Neural Networks.

Hybrid systems for prediction-a case study of predicting effluent flow to a sewage plant

Nikola K. Kasabov, Andrew R. Gray, Max Bailey, 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

Incremental linear discriminant analysis for classification of data streams

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Exploring Associations between Changes in Ambient Temperature and Stroke Occurrence: Comparative Analysis Using Global and Personalised Modelling Approaches

Nikola K. Kasabov, Valery Feigin, Yingjie Hu, 2011, ICONIP.

Towards a Wearable Coach: Classifying Sports Activities with Reservoir Computing

Dave Parry, Stefan Schliebs, Nikola K. Kasabov, 2013, EANN.

Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification

Nikola K. Kasabov, Josafath Israel Espinosa Ramos, Adam Osseiran, 2020, Sensors.

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, N. Kasabov, 2015, ICONIP.

To spike or not to spike: A probabilistic spiking neuron model

Nikola K. Kasabov, N. Kasabov, 2010, Neural Networks.

EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube

Hideaki Kawano, Maryam Gholami Doborjeh, Nikola K. Kasabov, 2017, ICONIP.

Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression

Maryam Gholami Doborjeh, Nikola K. Kasabov, Grace Y. Wang, 2019, ICONIP.

Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, 2009 International Joint Conference on Neural Networks.

Evolving fuzzy neural network for camera operations recognition

Irena Koprinska, Nikola K. Kasabov, N. Kasabov, 2000, Proceedings 15th International Conference on Pattern Recognition. ICPR-2000.

EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation

Jin Hu, Nikola K. Kasabov, Zeng-Guang Hou, 2014, 5th IEEE RAS/EMBS International Conference on Biomedical Robotics and Biomechatronics.

From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition

Nikola K. Kasabov, Richard Kilgour, S. J. Sinclair, 1999, Fuzzy Sets Syst..

Integrated Feature Selection and Parameter Optimization for Evolving Spiking Neural Networks Using Quantum Inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2009, 2009 International Conference of Soft Computing and Pattern Recognition.

EEG Classification with BSA Spike Encoding Algorithm and Evolving Probabilistic Spiking Neural Network

Nikola K. Kasabov, Nuttapod Nuntalid, Kshitij Dhoble, 2011, ICONIP.

Classification consistency analysis for bootstrapping gene selection

Shaoning Pang, Nikola K. Kasabov, Yingjie Hu, 2007, Neural Computing and Applications.

Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2006, Artif. Intell. Medicine.

Probabilistic Evolving Spiking Neural Network Optimization Using Dynamic Quantum-inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2010, Aust. J. Intell. Inf. Process. Syst..

Deep Learning in Spiking Neural Networks for Brain-Inspired Artificial Intelligence

Nikola K. Kasabov, 2018, CompSysTech.

Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system

Maryam Gholami Doborjeh, Nikola K. Kasabov, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Multi-Spectral Image Change Detection Based on Band Selection and Single-Band Iterative Weighting

Zhenhong Jia, Nikola K. Kasabov, Jie Yang, 2019, IEEE Access.

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework

Nikola K. Kasabov, N. Kasabov, 2008, International Conference on Neural Information Processing.

Correlation-aided support vector regression for forex time series prediction

Shaoning Pang, Lei Song, Nikola K. Kasabov, 2011, Neural Computing and Applications.

Discrete Sparse Hashing for Cross-Modal Similarity Search

Lu Wang, Jie Yang, Chao Ma, 2018, ICONIP.

Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data

Jin Hu, Muhaini Othman, Nikola K. Kasabov, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks

Jin Hu, Long Cheng, Nikola K. Kasabov, 2013, ICONIP.

Spike-time encoding as a data compression technique for pattern recognition of temporal data

Nikola K. Kasabov, Neelava Sengupta, N. Kasabov, 2017, Inf. Sci..

Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework

Jie Yang, Nikola K. Kasabov, Enmei Tu, 2014, ICONIP.

Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data

Nikola K. Kasabov, Vishal Jain, Zeke S. H. Chan, 2008, Appl. Soft Comput..

Are probabilistic spiking neural networks suitable for reservoir computing?

Stefan Schliebs, Nikola K. Kasabov, Ammar Mohemmed, 2011, The 2011 International Joint Conference on Neural Networks.

Bayesian learning of sparse gene regulatory networks

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2007, Biosyst..

TTLSC - Transductive Total Least Square Model for Classification and Its Application in Medicine

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2006, ADMA.

Evolving Integrative Brain-, Gene-, and Quantum Inspired Systems for Computational Intelligence and Knowledge Engineering

Nikola K. Kasabov, 2010, KES.

String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Haza Nuzly Abdul Hamed, 2009, ICONIP.

Preface

Nikola K. Kasabov, Takeshi Yamakawa, 1996, Fuzzy Sets Syst..

Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks

Nikola K. Kasabov, Elisa Capecci, Durgesh Nandini, 2018, ICONIP.

Global, local and personalised modeling and pattern discovery in bioinformatics: An integrated approach

Nikola K. Kasabov, N. Kasabov, 2007, Pattern Recognit. Lett..

Connectionist expert systems

Lakhmi C. Jain, Nikola K. Kasabov, 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks

Javier Del Ser, Nikola K. Kasabov, Jesus L. Lobo, 2018, IDC.

Hybrid systems for medical data analysis and decision making-a case study on varicose vein disorders

Nikola K. Kasabov, Max Bailey, Clive Solomon, 1995, Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

Hierarchical discrete systems and realisation of parallel algorithms

Nikola K. Kasabov, G. T. Bijev, B. J. Jechev, 1981, CONPAR.

Analyzing the dynamics of the simultaneous feature and parameter optimization of an evolving Spiking Neural Network

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Prognostic Expert Systems on a Hybrid Connectionist Environment

Nikola K. Kasabov, Daniel Nikovski, 1992, AIMSA.

DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction

Nikola K. Kasabov, Qun Song, N. Kasabov, 2002, IEEE Trans. Fuzzy Syst..

SVMT-Rule: Association Rule Mining Over SVM Classification Trees

Shaoning Pang, Nikola K. Kasabov, 2008, Rule Extraction from Support Vector Machines.

Evolutionary Computation For On-Line And Off-Line Parameter Tuning Of Evolving Fuzzy Neural Networksc

Nikola K. Kasabov, Zeke S. H. Chan, 2004, Int. J. Comput. Intell. Appl..

Tuning N-gram String Kernel SVMs via Meta Learning

Shaoning Pang, Nikola K. Kasabov, Nuwan Gunasekara, 2010, ICONIP.

FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition

Michael J. Watts, Nikola K. Kasabov, Andrew R. Gray, 1997, Inf. Sci..

Effective and Adaptive Learning Based on Diversive/Specific Curiosity

Shaoning Pang, Takeshi Yamakawa, Nikola K. Kasabov, 2010, Brain-Inspired Information Technology.

An Incremental Principal Component Analysis for Chunk Data

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2006, 2006 IEEE International Conference on Fuzzy Systems.

Evolving connectionist systems: A theory and a case study on adaptive speech recognition

Nikola K. Kasabov, N. Kasabov, 1999, IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339).

Fril - Fuzzy and Evidential Reasoning in Artificial Intelligence, by J. F. Baldwin, T. P. Martin, and B. W. Pilsworth

Nikola K. Kasabov, 1996, J. Am. Soc. Inf. Sci..

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, N. Kasabov, 2005, J. Bioinform. Comput. Biol..

Optimization of Spiking Neural Networks with dynamic synapses for spike sequence generation using PSO

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2011, The 2011 International Joint Conference on Neural Networks.

A novel graph-based k-means for nonlinear manifold clustering and representative selection

Longbing Cao, Jie Yang, Nikola K. Kasabov, 2014, Neurocomputing.

Reduced feature-set based parallel CHMM speech recognition systems

Waleed H. Abdulla, Nikola K. Kasabov, W. Abdulla, 2003, Inf. Sci..

A Multi-Information Fusion Correlation Filters Tracker

Nikola K. Kasabov, Zhenhong Jia, Huicheng Lai, 2020, IEEE Access.

Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions

Nikola K. Kasabov, N. Kasabov, 2015, Knowl. Based Syst..

Probabilistic Computational Neurogenetic Modeling: From Cognitive Systems to Alzheimer's Disease

Nikola K. Kasabov, Hiroshi Kojima, Reinhard Schliebs, 2011, IEEE Transactions on Autonomous Mental Development.

Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2007, ICONIP.

Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data

Francesco Carlo Morabito, Nikola K. Kasabov, Maurizio Fiasché, 2009, ICANN.

Incremental learning of feature space and classifier for face recognition

Shigeo Abe, Shaoning Pang, Nikola K. Kasabov, 2005, Neural Networks.

Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance

Jie Yang, Nikola K. Kasabov, Enmei Tu, 2015, Neurocomputing.

Correlation Filters with Adaptive Memories and Fusion for Visual Tracking

Jie Yang, Nikola K. Kasabov, Cheng Peng, 2017, ICONIP.

Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast

Zhenhong Jia, Xizhong Qin, Jie Yang, 2015, Int. J. Imaging Syst. Technol..

Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data

Hao Wu, Nikola K. Kasabov, Lin Gao, 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

FaNeuRobot: A Framework for Robot and Prosthetics Control Using the NeuCube Spiking Neural Network Architecture and Finite Automata Theory

Nikola K. Kasabov, Kaushalya Kumarasinghe, Denise Taylor, 2018, 2018 IEEE International Conference on Robotics and Automation (ICRA).

An Agent Based Framework for Modular Speech Recognition and Language Processing Systems

Nikola K. Kasabov, Andrew R. Gray, Richard Kilgour, 1997, International Conference on Neural Information Processing.

Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data

Jie Yang, Nikola K. Kasabov, Enmei Tu, 2017, IEEE Transactions on Neural Networks and Learning Systems.

The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems

Nikola K. Kasabov, N. Kasabov, 1998, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Learning Strategies for Modular Neuro-Fuzzy Systems: A Case Study on Phoneme-Based Speech Recognition

Nikola K. Kasabov, 1997, J. Intell. Fuzzy Syst..

Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic

Nikola K. Kasabov, N. Kasabov, 2015, Handbook of Computational Intelligence.

Spoken language analysis, modeling and recognition - Cstatistical and adaptive connectionist approaches

Nikola K. Kasabov, N. Kasabov, 2003, Information Sciences.

Object Motion Deblurring in Single Image Under Static Background

Nikola K. Kasabov, Zhenhong Jia, Jie Yang, 2020, IEEE Access.

Robust Kernel Approximation for Classification

Jie Yang, Nikola K. Kasabov, Xiaolin Huang, 2017, ICONIP.

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)

Zhenhong Jia, Xizhong Qin, Nikola K. Kasabov, 2017, 计算机科学.

Computational Neurogenetic Modelling: a Pathway to New Discoveries in Genetic Neuroscience

Simei Gomes Wysoski, Nikola K. Kasabov, Vishal Jain, 2006, Int. J. Neural Syst..

Incremental learning algorithm for spatio-temporal spike pattern classification

Nikola K. Kasabov, Ammar Mohemmed, N. Kasabov, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Guest Editorial Evolving Fuzzy Systems–-Preface to the Special Section

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2008, IEEE Transactions on Fuzzy Systems.

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, 2003, APBC.

Evolving Brain-Gene Ontology System (EBGOS): Towards Integrating Bioinformatics and Neuroinformatics Data to Facilitate Discoveries

Simei Gomes Wysoski, Nikola K. Kasabov, Vishal Jain, 2007, 2007 International Joint Conference on Neural Networks.

Adaptive cow movement detection using evolving spiking neural network models

Tao Gao, Nikola K. Kasabov, N. Kasabov, 2016, Evol. Syst..

sEMG-based torque estimation for robot-assisted lower limb rehabilitation

Jin Hu, Nikola K. Kasabov, Zeng-Guang Hou, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

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, Nikola K. Kasabov, Bruce Russell, 2016, IEEE Transactions on Biomedical Engineering.

Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning

Giacomo Indiveri, Nikola K. Kasabov, Nuttapod Nuntalid, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Investigating LLE Eigenface on Pose and Face Identification

Shaoning Pang, Nikola K. Kasabov, 2006, ISNN.

Application of an Improved Focal Loss in Vehicle Detection

Nikola K. Kasabov, Xuanlin He, Jie Yang, 2020, ICAISC.

Hybrid intelligent adaptive systems: A framework and a case study on speech recognition

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 1998, Int. J. Intell. Syst..

Evolving spiking neural networks for taste recognition

Simei Gomes Wysoski, Snjezana Soltic, Nikola K. Kasabov, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Spanning SVM Tree for Personalized Transductive Learning

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2009, ICANN.

Functionally reconfigurable general purpose parallel machines and some image processing and pattern recognition applications

Nikola K. Kasabov, N. Kasabov, 1985, Pattern Recognit. Lett..

A Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction

Russel Pears, Nikola K. Kasabov, Lukas, 2009, ICONIP.

Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems

Nikola K. Kasabov, Daniel Nikovski, Emilian Peev, 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

String Kernel Based SVM for Internet Security Implementation

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2009, ICONIP.

On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2006, ICANN.

Abnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation

Yu Zhao, Jie Yang, Nikola K. Kasabov, 2015, ICONIP.

Evolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition

Nikola K. Kasabov, Nuttapod Nuntalid, Kshitij Dhoble, 2011, ICONIP.

Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery

Shaoning Pang, Nikola K. Kasabov, Vishal Jain, 2006, PRIB.

A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking

Zhenhong Jia, Lu Liu, Jie Yang, 2015, Int. J. Imaging Syst. Technol..

A spiking neural network model for obstacle avoidance in simulated prosthetic vision

Jie Yang, Nikola K. Kasabov, Chenjie Ge, 2017, Inf. Sci..

Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks

Nikola K. Kasabov, Josafath Israel Espinosa Ramos, Elisa Capecci, 2019, Evolving Systems.

SAR Image Change Detection Based on Mathematical Morphology and the K-Means Clustering Algorithm

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2019, IEEE Access.

An efficient greedy K-means algorithm for global gene trajectory clustering

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2006, Expert Syst. Appl..

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

Nikola K. Kasabov, Elisa Capecci, Grace Y. Wang, 2015, Neural Networks.

Knowledge Extraction from Evolving Spiking Neural Networks with Rank Order Population Coding

Snjezana Soltic, Nikola K. Kasabov, N. Kasabov, 2010, Int. J. Neural Syst..

Connectionist Fuzzy Production Systems

Nikola K. Kasabov, 1993, Fuzzy Logic in Artificial Intelligence.

FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network

Nikola K. Kasabov, Clarence Tan, Narayan Puthanmadam Subramaniyam, 2020, Sensors.

Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture

Francesco Carlo Morabito, Jonas Duun-Henriksen, Nikola K. Kasabov, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

A Fast Sand-Dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering

Nikola K. Kasabov, Yaqiao Cheng, Zhenhong Jia, 2020, IEEE Access.

Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends

Russel Pears, Nikola K. Kasabov, Harya Widiputra, 2011, PAKDD.

Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework

Mariette Awad, Nikola K. Kasabov, Obada Al Zoubi, 2018, Artif. Intell. Medicine.

Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2012, Int. J. Neural Syst..

Ontology-Based Framework for Personalized Diagnosis and Prognosis of Cancer Based on Gene Expression Data

Nikola K. Kasabov, Yingjie Hu, 2007, ICONIP.

NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals

Nikola K. Kasabov, N. Kasabov, 2012, ANNPR.

MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules

Nikola K. Kasabov, Qun Song, Yuan-Chun Hwang, 2008, 2008 IEEE International Conference on Fuzzy Systems (IEEE World Congress on Computational Intelligence).

Reservoir-Based Evolving Spiking Neural Network for Spatio-temporal Pattern Recognition

Stefan Schliebs, Nikola K. Kasabov, Haza Nuzly Abdul Hamed, 2011, ICONIP.

Poisson Image Denoising Based on BLS-GSM Method

Jie Yang, Nikola K. Kasabov, Zhenghong Jia, 2015, ICONIP.

ESOM: an algorithm to evolve self-organizing maps from online data streams

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Identifying overlapping mutated driver pathways by constructing gene networks in cancer

Hao Wu, Feng Li, Xiaofei Yang, 2015, BMC Bioinformatics.

TWNFI - a transductive neuro-fuzzy inference system with weighted data normalization for personalized modeling

Nikola K. Kasabov, Qun Song, 2006, Neural Networks.

An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification

Nikola K. Kasabov, Siti Mariyam Hj. Shamsuddin, Harya Widiputra, 2011, The 2011 International Joint Conference on Neural Networks.

Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis

Shaoning Pang, Nikola K. Kasabov, Ilkka Havukkala, 2006, ISNN.

Towards Spatio-Temporal Pattern Recognition Using Evolving Spiking Neural Networks

Stefan Schliebs, Nikola K. Kasabov, Nuttapod Nuntalid, 2010, ICONIP.

Evolving spiking neural networks for audiovisual information processing

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2010, Neural Networks.

Ensembles of EFuNNs: an architecture for a multimodule classifier

Nikola K. Kasabov, Brendon J. Woodford, 2001, 10th IEEE International Conference on Fuzzy Systems. (Cat. No.01CH37297).

Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection

Nikola K. Kasabov, Elisa Capecci, Lucien Koefoed, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application

Robert Kozma, Nikola K. Kasabov, Tico Cohen, 2001, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Statistical, connectionist, and fuzzy inference techniques for image classification

Nikola K. Kasabov, Steven A. Israel, 1997, J. Electronic Imaging.

Editorial

Shaoning Pang, Nikola K. Kasabov, 1981, Signs: Journal of Women in Culture and Society.

NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data

Nikola K. Kasabov, N. Kasabov, 2014, Neural Networks.

Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue

Nikola K. Kasabov, Matthias E. Futschik, Anthony Reeve, 2003, Artif. Intell. Medicine.

An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks

Russel Pears, Nikola K. Kasabov, Fahad Bashir Alvi, 2018, Evol. Syst..

Fast neural network ensemble learning via negative-correlation data correction

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, IEEE Transactions on Neural Networks.

Integration of connectionist methods and chaotic time‐series analysis for the prediction of process data

Robert Kozma, Nikola K. Kasabov, J. S. Kim, 1998, Int. J. Intell. Syst..

Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke

Muhaini Othman, Nikola K. Kasabov, Zeng-Guang Hou, 2014, Neurocomputing.

Incremental and decremental LDA learning with applications

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2010, The 2010 International Joint Conference on Neural Networks (IJCNN).

Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series

Lorenzo Bruzzone, Nikola K. Kasabov, Reggio N. Hartono, 2016, IEEE Transactions on Geoscience and Remote Sensing.

Special Issue on Advanced Neuro-Fuzzy Techniques and Their Applications: Introduction

Kaoru Hirota, Nikola K. Kasabov, K. Hirota, 1997, Information Sciences.

Sleep Stage Classification using NeuCube on SpiNNaker: a Preliminary Study

Maryam Gholami Doborjeh, Nikola K. Kasabov, Basabdatta Sen Bhattacharya, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification pdf

Lin Zhu, Jie Yang, Nikola K. Kasabov, 2016, Inf. Sci..

Neuro-Fuzzy and Multivariate Statistical Classification of Fruit Populations Based on Visible-Near Infrared Spectrophotometry Data

Jaesoo Kim, Nikola K. Kasabov, A. Mowat, 1997, International Conference on Neural Information Processing.

An Evolving Neural Network Model for Person Verification Combining Speech and Image

David Zhang, Nikola K. Kasabov, Akbar Ghobakhlou, 2004, ICONIP.

Fast and adaptive network of spiking neurons for multi-view visual pattern recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2008, Neurocomputing.

TWNFC - Transductive Neural-Fuzzy Classifier with Weighted Data Normalization and Its Application in Medicine

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2005, International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC'06).

Discovering Rules of Adaptation and Interaction: From Molecules and Gene Interaction to Brain Functions

Nikola K. Kasabov, 2004, HIS.

Method for Training a Spiking Neuron to Associate Input-Output Spike Trains

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2011, EANN/AIAI.

Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, ICONIP.

Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems

Nikola K. Kasabov, N. Kasabov, 2006, Appl. Soft Comput..

AVIS: a connectionist-based framework for integrated auditory and visual information processing

Eric O. Postma, H. Jaap van den Herik, Nikola K. Kasabov, 2000, Inf. Sci..

Coevolutionary Method for Gene Selection and Parameter Optimization in Microarray Data Analysis

Nikola K. Kasabov, Yingjie Hu, 2009, ICONIP.

Evolving spiking neural network—a survey

Stefan Schliebs, Nikola K. Kasabov, N. Kasabov, 2013, Evolving Systems.

EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2018, 2018 International Joint Conference on Neural Networks (IJCNN).

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, 2018, Evol. Syst..

Introduction: Hybrid intelligent adaptive systems

Robert Kozma, Nikola K. Kasabov, 1998, Int. J. Intell. Syst..

Integrative connectionist learning systems inspired by nature: current models, future trends and challenges

Nikola K. Kasabov, N. Kasabov, 2009, Natural Computing.

Artificial Neural Networks and Expert Systems (Annes '93)

Nikola K. Kasabov, N. Kasabov, 1993 .

Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries

Nikola K. Kasabov, Vishal Jain, Frances Joseph, 2006, 2006 Sixth International Conference on Hybrid Intelligent Systems (HIS'06).

Adaptive Training of Radial Basis Function Networks Based on Cooperative Evolution and Evolutionary Programming

Nikola K. Kasabov, Alexander P. Topchy, Victor V. Miagkikh, 1997, ICONIP.

Adaptive Location for Multiple Salient Objects Detection

Jie Yang, Yun Gu, Nikola K. Kasabov, 2015, ICONIP.

Change Detection in Multitemporal Monitoring Images Under Low Illumination

Nikola K. Kasabov, Zhenhong Jia, Jie Yang, 2020, IEEE Access.

Training spiking neural networks to associate spatio-temporal input-output spike patterns

Stefan Schliebs, Nikola K. Kasabov, Satoshi Matsuda, 2013, Neurocomputing.

Enhancing recognition systems through an integrated processing of visual and audio information

Eric O. Postma, H. Jaap van den Herik, Nikola K. Kasabov, 1998, SMC'98 Conference Proceedings. 1998 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.98CH36218).

Special Issue: Contemporary development of neural computation and applications

Bruno Apolloni, Nikola K. Kasabov, Ivan Jordanov, 2012, Neural Computing and Applications.

Quantum-Inspired Evolutionary Algorithm: A Multimodel EDA

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, IEEE Transactions on Evolutionary Computation.

BRAIN GENE ONTOLOGY AND SIMULATION SYSTEM (BGOS) FOR A BETTER UNDERSTANDING OF THE BRAIN

Nikola K. Kasabov, Vishal Jain, Frances Joseph, 2007, Cybern. Syst..

Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition

Nikola K. Kasabov, N. Kasabov, 2012, 2012 6th IEEE International Conference Intelligent Systems.

Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks

Javier Del Ser, Nikola K. Kasabov, Elisa Capecci, 2018, IDC.

Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems

Nikola K. Kasabov, N. Kasabov, 1996, Fuzzy Sets Syst..

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, 2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS).

Spiking Neural Network for On-line Cognitive Activity Classification Based on EEG Data

Stefan Schliebs, Nikola K. Kasabov, Elisa Capecci, 2013, ICONIP.

Image Processing of Porous Silicon Microarray in Refractive Index Change Detection

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2017, Sensors.

Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model

Francesco Carlo Morabito, Nikola K. Kasabov, Elisa Capecci, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm

Nikola K. Kasabov, N. Kasabov, 1998, ICONIP.

Incremental Learning of Chunk Data for Online Pattern Classification Systems

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, IEEE Transactions on Neural Networks.

An enhanced multiphase Chan–Vese model for the remote sensing image segmentation

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2014, Concurr. Comput. Pract. Exp..

Modeling the emergence of bilingual acoustic clusters: a preliminary case study

Nikola K. Kasabov, Richard Kilgour, Mark R. Laws, 2003, Inf. Sci..

Personalised Modelling for Multiple Time-Series Data Prediction: A Preliminary Investigation in Asia Pacific Stock Market Indexes Movement

Russel Pears, Nikola K. Kasabov, Harya Widiputra, 2008, ICONIP.

TWRBF - Transductive RBF Neural Network with Weighted Data Normalization

Nikola K. Kasabov, Qun Song, N. Kasabov, 2004, ICONIP.

Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2017, IEEE Transactions on Neural Networks and Learning Systems.

A Hybrid Genetic Algorithm and Expectation Maximization Method for Global Gene Trajectory Clustering

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2005, J. Bioinform. Comput. Biol..

Methods and systems for intelligent human-computer interaction

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 2000, Inf. Sci..

Short-term ANN load forecasting from limited data using generalization learning strategies

Nikola K. Kasabov, Zeke S. H. Chan, Ahmad B. Rad, 2006, Neurocomputing.

A method used for Dotted Data Matrix image processing

Tao Gao, Nikola K. Kasabov, 2015, J. Comput. Methods Sci. Eng..

Gene Regulatory Network Discovery from Time-Series Gene Expression Data - A Computational Intelligence Approach

Nikola K. Kasabov, Vishal Jain, Zeke S. H. Chan, 2004, ICONIP.

An evolving localised learning model for on-line image colour quantisation

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

Contrast enhancement of medical images using fuzzy set theory and nonsubsampled shearlet transform

Nikola K. Kasabov, Jia Zhenhong, Yang Jie, 2019, Int. J. Imaging Syst. Technol..

Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition

Nikola K. Kasabov, N. Kasabov, 2012, WCCI.

A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD)

Nikola K. Kasabov, Zeke S. H. Chan, 2005, Neural Processing Letters.

HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems

Nikola K. Kasabov, Jaesoo Kim, N. Kasabov, 1999, Neural Networks.

A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2004, PRICAI.

Personalised Modelling on SNPs Data for Crohn's Disease Prediction

Nikola K. Kasabov, Yingjie Hu, N. Kasabov, 2011, ICONIP.

A Hybrid Feature Selection Approach for Microarray Gene Expression Data

Liang Goh, Nikola K. Kasabov, Qun Song, 2006, International Conference on Computational Science.

The Application of Hybrid Evolving Connectionist Systems to Image Classification

Nikola K. Kasabov, Brendon J. Woodford, Steven A. Israel, 2000, J. Adv. Comput. Intell. Intell. Informatics.

Genetic Algorithms for the Design of Fuzzy Neural Networks

Michael J. Watts, Nikola K. Kasabov, N. Kasabov, 1998, ICONIP.

Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model

Maryam Gholami Doborjeh, Nikola K. Kasabov, Elisa Capecci, 2014, 2014 IEEE Symposium on Evolving and Autonomous Learning Systems (EALS).

Brain-Like Evolving Spiking Neural Networks for Multimodal Information Processing

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2010, Brain-Inspired Information Technology.

A Membership Function Selection Method for Fuzzy Neural Networks

Martin K. Purvis, Nikola K. Kasabov, Quingqing Zhou, 1997, ICONIP.

Hybrid system for robust recognition of noisy speech based on evolving fuzzy neural networks and adaptive filtering

Nikola K. Kasabov, Georgi Iliev, N. Kasabov, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Dynamic interaction networks in modelling and predicting the behaviour of multiple interactive stock markets

Russel Pears, Nikola K. Kasabov, Antoaneta Serguieva, 2009, Intell. Syst. Account. Finance Manag..

Integrating evolving brain – gene ontology and connectionist-based system for modeling and knowledge discovery

Nikola K. Kasabov, Vishal Jain, Lubica Benusková, 2008 .

Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications

Jin Hu, Nikola K. Kasabov, Zeng-Guang Hou, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework

Nikola K. Kasabov, N. Kasabov, 2008, ICONIP.

Model for exploiting associative matching in AI production systems

Nikola K. Kasabov, Simon H. Lavington, C. Wang, 1995, Knowl. Based Syst..

Unsupervised Segmentation Using Cluster Ensembles

Wei Zhang, Zhenhong Jia, Jie Yang, 2014, ICONIP.

Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach

Nikola K. Kasabov, Qun Song, Elaine Rush, 2008, Aust. J. Intell. Inf. Process. Syst..

Neural Networks and Logic Programming - a Hybrid Model and its Applicability to Building Expert Systems

Nikola K. Kasabov, S. H. Petkov, N. Kasabov, 1992, European Conference on Artificial Intelligence.

Evolving Spiking Neural Networks for online learning over drifting data streams

Javier Del Ser, Nikola K. Kasabov, Jesus L. Lobo, 2018, Neural Networks.

Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach

Francesco Carlo Morabito, Nikola K. Kasabov, Maurizio Fiasché, 2009, ICONIP.

Adaptive modeling and discovery in bioinformatics: The evolving connectionist approach

Nikola K. Kasabov, N. Kasabov, 2008, Int. J. Intell. Syst..

A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG)

Nikola K. Kasabov, Peng Du, Vivienne Breen, 2016, ANNPR.

An adaptive model of person identification combining speech and image information

David Zhang, Nikola K. Kasabov, Akbar Ghobakhlou, 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2019, Sensors.

Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes

Nikola K. Kasabov, Elisa Capecci, N. Kasabov, 2015, Inf. Sci..

Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture

Nikola K. Kasabov, Norhanifah Murli, Bana Handaga, 2014, ICONIP.

Quasi-Noise-Free and Detail-Preserved Digital Holographic Reconstruction

Zhenhong Jia, Nikola K. Kasabov, Jie Yang, 2019, IEEE Access.

eSNN for Spatio-Temporal fMRI Brain Pattern Recognition with a Graphical Object Recognition Case Study

Nikola K. Kasabov, Norhanifah Murli, Nurul Amirah Paham, 2020, SCDM.

Evolving Connectionist and Hybrid Systems: Methods, Tools, Applications

Nikola K. Kasabov, 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).

Evolving connectionist systems - the knowledge engineering approach (2. ed.)

Nikola K. Kasabov, N. Kasabov, 2007 .

Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning

Nikola K. Kasabov, N. Kasabov, 2001, IEEE Trans. Syst. Man Cybern. Part B.

Incremental learning of feature space and classifier for on-line pattern recognition

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2006, Int. J. Knowl. Based Intell. Eng. Syst..

Computational Intelligence for Bioinformatics: The Knowledge Engineering Approach

Nikola K. Kasabov, 2005, SGAI Conf..

Learning fuzzy rules through neural networks

Nikola K. Kasabov, N. Kasabov, 1993, Proceedings 1993 The First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems.

LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2012, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

Video Snow Removal Based on Self-Adaptation Snow Detection and Patch-Based Gaussian Mixture Model

Nikola K. Kasabov, Zhenhong Jia, Jie Yang, 2020, IEEE Access.

Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application

Zhenhong Jia, Jie Yang, Nikola K. Kasabov, 2017, Sensors.

Adaptive incremental principal component analysis in nonstationary online learning environments

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2009, 2009 International Joint Conference on Neural Networks.

Vision Based Mobile Robot for Indoor Environmental Security

Shaoning Pang, Takeshi Yamakawa, Nikola K. Kasabov, 2008, ICONIP.

A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI

Jie Yang, Nikola K. Kasabov, Hao Zheng, 2018, ICONIP.

Computational neurogenetic modeling: integration of spiking neural networks, gene networks, and signal processing techniques

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2004, IEEE International Workshop on Biomedical Circuits and Systems, 2004..

Integration of Brain-Gene Ontology and Simulation Systems for Learning, Modelling and Discovery

Nikola K. Kasabov, Vishal Jain, Frances Joseph, 2008, Computational Intelligence in Medical Informatics.

Evaluating SPAN Incremental Learning for Handwritten Digit Recognition

Nikola K. Kasabov, Guoyu Lu, Ammar Mohemmed, 2012, ICONIP.

Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2006, ACIVS.

Integrated optimisation method for personalised modelling and case studies for medical decision support

Nikola K. Kasabov, Yingjie Hu, 2010, Int. J. Funct. Informatics Pers. Medicine.

Extracting temporal knowledge from time series: A case study in ecological data

Susan P. Worner, Russel Pears, Nikola K. Kasabov, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

On the Probabilistic Optimization of Spiking Neural Networks

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2010, Int. J. Neural Syst..

Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling

Stefan Schliebs, Nikola K. Kasabov, Ammar Mohemmed, 2011, CIBB.

Future directions for intelligent systems and information sciences : the future of speech and image technologies, brain computers, www, and bioinformatics

Nikola K. Kasabov, N. Kasabov, 2000 .

A two-stage methodology for gene regulatory network extraction from time-course gene expression data

Nikola K. Kasabov, Zeke S. H. Chan, Lesley Collins, 2004, IEEE International Workshop on Biomedical Circuits and Systems, 2004..

Global EM Learning of Finite Mixture Models using the Greedy Elimination Method

Nikola K. Kasabov, Zeke S. H. Chan, N. Kasabov, 2005, SGAI Conf..

Modeling L-LTP based on changes in concentration of pCREB transcription factor

Nikola K. Kasabov, Lubica Benusková, N. Kasabov, 2007, Neurocomputing.

An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition

Yu Cheng, Tao Gao, Nikola K. Kasabov, 2016, Neurocomputing.

NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data

Susan P. Worner, Muhaini Othman, Jie Yang, 2014, 2014 International Joint Conference on Neural Networks (IJCNN).

NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation

Giacomo Indiveri, Nikola K. Kasabov, Nathan Matthew Scott, 2013, ICONIP.

Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2018, Cognitive Computation.

Multi-Agent Implementation of Fractal Analysis by Fuzzy Neural Networks

Robert Kozma, Nikola K. Kasabov, J. A. Swope, 1997, International Conference on Neural Information Processing.

Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities

Nikola K. Kasabov, N. Kasabov, 2007, Challenges for Computational Intelligence.

Editorial

Plamen P. Angelov, Dimitar Filev, Nikola K. Kasabov, 2010, Evolutionary Systematics.

Personalized mode transductive spanning SVM classification tree

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2011, Inf. Sci..

Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis: A Computational Framework Proposed

Francesco Carlo Morabito, Nikola K. Kasabov, Maurizio Fiasché, 2010, Aust. J. Intell. Inf. Process. Syst..

NFI: a neuro-fuzzy inference method for transductive reasoning

Nikola K. Kasabov, Qun Song, N. Kasabov, 2005, IEEE Transactions on Fuzzy Systems.

Editorial: Self-Organization and Adaptation in Intelligent Systems

Robert Kozma, Nikola K. Kasabov, N. Kasabov, 1998, Journal of Advanced Computational Intelligence and Intelligent Informatics.

Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture

Nikola K. Kasabov, Neelava Sengupta, Anne Abbott, 2016, 2016 International Joint Conference on Neural Networks (IJCNN).

Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2009, Neural Networks.

Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples

Jin Hu, Nikola K. Kasabov, Nathan Matthew Scott, 2013, ICONIP.

A Fast Image Segmentation Algorithm Based on Saliency Map and Neutrosophic Set Theory

Nikola K. Kasabov, Jie Yang, Sensen Song, 2020, IEEE Photonics Journal.

r-SVMT: Discovering the knowledge of association rule over SVM classification trees

Shaoning Pang, Nikola K. Kasabov, N. Kasabov, 2008, 2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence).

Hideaki Kawano, Maryam Gholami Doborjeh, Nikola K. Kasabov, 2016, ICONIP.

Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2007, ICONIP.

Chunk Incremental LDA Computing on Data Streams

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2005, ISNN.

SPAN: A Neuron for Precise-Time Spike Pattern Association

Stefan Schliebs, Nikola K. Kasabov, Ammar Mohemmed, 2011, ICONIP.

A Methodology and a System for Adaptive, Integrated Speech and Image Learning and Recognition

Nikola K. Kasabov, Akbar Ghobakhlou, 2004, Int. J. Comput. Syst. Signals.

Text-Independent Speaker Authentication with Spiking Neural Networks

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2007, ICANN.

Factorizing Class Characteristics via Group MEBs Construction

Shaoning Pang, Nikola K. Kasabov, Ye Chen, 2010, ICONIP.

A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks

Michael J. Watts, Robert Kozma, Nikola K. Kasabov, 1997, International Conference on Neural Information Processing.

Hybrid Connectionist Fuzzy Systems for Speech Recognition and the Use of Connectionist Production Systems

Nikola K. Kasabov, 1994, IEEE/Nagoya-University World Wisepersons Workshop.

Salient Object Segmentation Based on Automatic Labeling

Jie Yang, Chen Gong, Yu Qiao, 2013, ICONIP.

Evolving integrated multi-model framework for on line multiple time series prediction

Russel Pears, Nikola K. Kasabov, Harya Widiputra, 2013, Evol. Syst..

Encoding and decoding the knowledge of association rules over SVM classification trees

Shaoning Pang, Nikola K. Kasabov, N. Kasabov, 2009, Knowledge and Information Systems.

Hybrid Connectionist Fuzzy Production System: Towards Building Comprehensive AI

Nikola K. Kasabov, 1995, Intell. Autom. Soft Comput..

Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network

Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov, 2008, ICONIP.

On-line pattern analysis by evolving self-organizing maps

Nikola K. Kasabov, Jeremiah D. Deng, N. Kasabov, 2003, Neurocomputing.

Personalized Modeling Based Gene Selection for Microarray Data Analysis

Nikola K. Kasabov, Yingjie Hu, Qun Song, 2008, ICONIP.

Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations

Simei Gomes Wysoski, Nikola K. Kasabov, Lubica Benusková, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

The Evolution of the Evolving Neuro-Fuzzy Systems: From Expert Systems to Spiking-, Neurogenetic-, and Quantum Inspired

Nikola K. Kasabov, N. Kasabov, 2013, On Fuzziness.

On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks

Nikola K. Kasabov, N. Kasabov, 2001, Neurocomputing.

One-Pass Incremental Membership Authentication by Face Classification

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2004, ICBA.

Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis

Nikola K. Kasabov, Elisa Capecci, Jack Dray, 2018, ICONIP.

Evolving Connectionist Systems for Adaptive Sport Coaching

Shaoning Pang, Stephen G. MacDonell, Nikola K. Kasabov, 2007, ICONIP.

A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors

Nikola K. Kasabov, Anne Wendt, Lukas Paulun, 2018, Front. Comput. Neurosci..

Simulation of ECB decisions and forecast of short term Euro rate with an adaptive fuzzy expert system

Nikola K. Kasabov, Mario Fedrizzi, Lorenzo Rizzi, 2003, Eur. J. Oper. Res..

A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering

Zhenhong Jia, Nikola K. Kasabov, Jie Yang, 2017, IEEE Access.

A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners pdf

Nikola K. Kasabov, Eva Portillo, Lucien Koefoed, 2019, Eur. J. Oper. Res..

Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks

Nikola K. Kasabov, Elisa Capecci, Imanol Bilbao, 2018, ICONIP.

Curiosity driven incremental LDA agent active learning

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2009, 2009 International Joint Conference on Neural Networks.

A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems

Shaoning Pang, Nikola K. Kasabov, Seiichi Ozawa, 2008, ICONIP.

Guest Editorial Special Issue on Computational Modeling of Neural and Brain Development

Yan Meng, Juyang Weng, Nikola K. Kasabov, 2011, IEEE Trans. Auton. Ment. Dev..

Dynamic Neuro-fuzzy Inference and Statistical Models for Risk Analysis of Pest Insect Establishment

Susan P. Worner, Shaoning Pang, Snjezana Soltic, 2004, ICONIP.

Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2016, ICONIP.

Adaptive speech recognition with evolving connectionist systems

Michael J. Watts, Nikola K. Kasabov, Akbar Ghobakhlou, 2003, Inf. Sci..

Evolving Connectionist Systems and Evolving Brains

Nikola K. Kasabov, N. Kasabov, 1998, International Conference on Neural Information Processing.

Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems

Nikola K. Kasabov, Seiichi Ozawa, Masayuki Hisada, 2010, Evol. Syst..

Hybrid Connectionist Rule-Based Systems

Nikola K. Kasabov, 1990, AIMSA.

Transductive Knowledge Based Fuzzy Inference System for Personalized Modeling

Nikola K. Kasabov, Qun Song, Tianmin Ma, 2005, FSKD.

A method for SIMD/MIMD functionally reconfigurable multimicroprocessor systems design and parallel data exchange algorithms

Nikola K. Kasabov, 1985, Parallel Comput..

Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning

Michael J. Watts, Robert Kozma, Nikola K. Kasabov, 1998, Inf. Sci..

Constructing Robust Liquid State Machines to Process Highly Variable Data Streams

Stefan Schliebs, Nikola K. Kasabov, Maurizio Fiasché, 2012, ICANN.

Hierarchical Core Vector Machines for Network Intrusion Detection

Shaoning Pang, Youki Kadobayashi, Nikola K. Kasabov, 2009, ICONIP.

Integrating Local and Personalised Modelling with Global Ontology Knowledge Bases for Biomedical and Bioinformatics Decision Support

Russel Pears, Stephen G. MacDonell, Nikola K. Kasabov, 2008, Computational Intelligence in Biomedicine and Bioinformatics.

An Effective Algorithm for Specular Reflection Image Enhancement

Nikola K. Kasabov, Jie Yang, Zhenhong Jia, 2021, IEEE Access.

Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model

Nikola K. Kasabov, Zhenhong Jia, Weijie Chen, 2022, Remote. Sens..

Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network

Nikola K. Kasabov, Jie Yang, Aiwen Jia, 2021, IEEE Access.

Stock market movement prediction using evolving spiking neural networks

Nikola K. Kasabov, Vadlamani Ravi, Akshay Raj Gollahalli, 2021, Handbook of Big Data Analytics Volume 2: Applications in ICT, security and business analytics.

Multispectral Image Change Detection Based on Single-Band Slow Feature Analysis

Nikola K. Kasabov, Jie Yang, Zhenhong Jia, 2021, Remote. Sens..

Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network

Maryam Gholami Doborjeh, Nikola K. Kasabov, Zohreh Gholami Doborjeh, 2021, Sensors.

NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns

Nikola K. Kasabov, Clarence Tan, Marko Sarlija, 2021, Neurocomputing.

Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives

Nikola K. Kasabov, Yawen Lu, Guoyu Lu, 2021, 2021 International Joint Conference on Neural Networks (IJCNN).

Multispectral Image Enhancement Based on Weighted Principal Component Analysis and Improved Fractional Differential Mask

Nikola K. Kasabov, Jie Yang, Zhenhong Jia, 2022, IEEE Geoscience and Remote Sensing Letters.

1993 the First New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, November 24-26, 1993, Dunedin, New Zealand : proceedings

Nikola K. Kasabov, N. Kasabov, 1993 .