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Nikola K. Kasabov
Person information
- affiliation: Auckland University of Technology, Knowledge Engineering & Discovery Research Institute (KEDRI), New Zealand
- affiliation: University of Otago, Department of Information Science, Dunedin, New Zealand
- affiliation (PhD 1975): Technical University Sofia, Bulgaria
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2020 – today
- 2024
- [j207]Yongji Li, Luping Wang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
Depth prior-based stable tensor decomposition for video snow removal. Displays 84: 102733 (2024) - [j206]Enlong Wang
, Jiawei Li
, Jia Lei
, Jinyuan Liu
, Shihua Zhou
, Bin Wang
, Nikola K. Kasabov
:
SDFuse: Semantic-injected dual-flow learning for infrared and visible image fusion. Expert Syst. Appl. 252: 124188 (2024) - [j205]Sensen Song, Zhenhong Jia
, Fei Shi, Junnan Wang, Jie Yang, Nikola K. Kasabov:
Saliency optimization fused background feature with frequency domain features. Multim. Tools Appl. 83(14): 40509-40528 (2024) - [j204]Xiaoxu Liu, Wei Qi Yan, Nikola K. Kasabov:
Moving vehicle tracking and scene understanding: A hybrid approach. Multim. Tools Appl. 83(17): 51541-51558 (2024) - [j203]Zhiqing Guo
, Zhenhong Jia
, Liejun Wang
, Dewang Wang
, Gaobo Yang
, Nikola K. Kasabov
:
Constructing New Backbone Networks via Space-Frequency Interactive Convolution for Deepfake Detection. IEEE Trans. Inf. Forensics Secur. 19: 401-413 (2024) - [j202]Dongdong Ni
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Online Low-Light Sand-Dust Video Enhancement Using Adaptive Dynamic Brightness Correction and a Rolling Guidance Filter. IEEE Trans. Multim. 26: 2192-2206 (2024) - 2023
- [j201]Alexander Hui Xiang Yang
, Nikola K. Kasabov
, Yusuf Özgür Çakmak:
Prediction and detection of virtual reality induced cybersickness: a spiking neural network approach using spatiotemporal EEG brain data and heart rate variability. Brain Informatics 10(1): 15 (2023) - [j200]Mark Crook-Rumsey
, Christina J. Howard
, Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Josafath Israel Espinosa Ramos, Nikola K. Kasabov, Alexander Sumich
:
Spatiotemporal EEG Dynamics of Prospective Memory in Ageing and Mild Cognitive Impairment. Cogn. Comput. 15(4): 1273-1299 (2023) - [j199]Piotr S. Maciag, Robert Bembenik, Aleksandra Piekarzewicz, Javier Del Ser, Jesus L. Lobo, Nikola K. Kasabov:
Effective air pollution prediction by combining time series decomposition with stacking and bagging ensembles of evolving spiking neural networks. Environ. Model. Softw. 170: 105851 (2023) - [j198]Plamen Angelov, Dimitar P. Filev, Nikola K. Kasabov, Daniel Leite
, Maharadhika Pratama, Susanne Saminger-Platz
, Erich-Peter Klement
:
Obituary Edwin Lughofer (1972-2023). Evol. Syst. 14(5): 747-748 (2023) - [j197]Aitor Martínez-Seras
, Javier Del Ser, Jesus L. Lobo, Pablo García Bringas, Nikola K. Kasabov:
A novel Out-of-Distribution detection approach for Spiking Neural Networks: Design, fusion, performance evaluation and explainability. Inf. Fusion 100: 101943 (2023) - [j196]Mingjian Chen, Hao Zheng, Changsheng Lu, Enmei Tu, Jie Yang, Nikola K. Kasabov
:
Accurate breast lesion segmentation by exploiting spatio-temporal information with deep recurrent and convolutional network. J. Ambient Intell. Humaniz. Comput. 14(12): 15609-15617 (2023) - [j195]Dongdong Ni, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
A real-time quality improvement method based on an adaptive dynamic screened Poisson equation for surveillance video in sand-dust weather. J. Real Time Image Process. 20(5): 105 (2023) - [j194]Fei Shi, Zhenhong Jia
, Huicheng Lai, Nikola K. Kasabov, Sensen Song, Junnan Wang:
Sand-dust image enhancement based on light attenuation and transmission compensation. Multim. Tools Appl. 82(5): 7055-7077 (2023) - [j193]Ye Xin, Yifei Wei, Zhuang Huang, Zhenhong Jia
, Jie Yang, Nikola K. Kasabov:
A fast and effective algorithm for specular reflection image enhancement. Multim. Tools Appl. 82(10): 14897-14914 (2023) - [j192]Dongdong Ni, Zhenhong Jia
, Jie Yang, Nikola K. Kasabov:
A fast sand-dust video quality improvement method using simple color balance and dynamic guided filtering. Multim. Tools Appl. 82(21): 33285-33302 (2023) - [j191]Xiang Wang
, Jie Yang, Nikola K. Kasabov
:
Integrating Spatial and Temporal Information for Violent Activity Detection from Video Using Deep Spiking Neural Networks. Sensors 23(9): 4532 (2023) - [j190]Wei Zhang
, Zhenhong Jia
, Jie Yang, Nikola K. Kasabov:
A dual channel decomposition and remapping fusion model for low illumination images with a wide field of view. Signal Process. Image Commun. 113: 116925 (2023) - [j189]Jiawei Li
, Jinyuan Liu
, Shihua Zhou
, Qiang Zhang, Nikola K. Kasabov
:
Learning a Coordinated Network for Detail-Refinement Multiexposure Image Fusion. IEEE Trans. Circuits Syst. Video Technol. 33(2): 713-727 (2023) - [j188]Baoqiang Shi, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov:
Unsupervised Change Detection in Wide-Field Video Images Under Low Illumination. IEEE Trans. Circuits Syst. Video Technol. 33(4): 1564-1576 (2023) - [j187]Sensen Song
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Image Segmentation Based on Fuzzy Low-Rank Structural Clustering. IEEE Trans. Fuzzy Syst. 31(7): 2153-2166 (2023) - [j186]Nikola K. Kasabov
, Yongyao Tan, Maryam Gholami Doborjeh, Enmei Tu
, Jie Yang
, Wilson Wen Bin Goh, Jimmy Lee
:
Transfer Learning of Fuzzy Spatio-Temporal Rules in a Brain-Inspired Spiking Neural Network Architecture: A Case Study on Spatio-Temporal Brain Data. IEEE Trans. Fuzzy Syst. 31(12): 4542-4552 (2023) - [j185]Jia Lei
, Jiawei Li
, Jinyuan Liu
, Shihua Zhou
, Qiang Zhang
, Nikola K. Kasabov
:
GALFusion: Multi-Exposure Image Fusion via a Global-Local Aggregation Learning Network. IEEE Trans. Instrum. Meas. 72: 1-15 (2023) - [c175]Sugam Budhraja
, Balkaran Singh, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Samuel Tan, Edmund Lai, Wilson Wen Bin Goh, Nikola K. Kasabov:
Mosaic LSM: A Liquid State Machine Approach for Multimodal Longitudinal Data Analysis. IJCNN 2023: 1-8 - [c174]Petia D. Koprinkova-Hristova, Dimitar P. Filev, Simona Nedelcheva, Svetlozar Yordanov, Nikola K. Kasabov:
On-line Learning, Classification and Interpretation of Brain Signals using 3D SNN and ESN. IJCNN 2023: 1-6 - [c173]Dimitar P. Filev, Petia D. Koprinkova-Hristova
, Nikola K. Kasabov
, Simona Nedelcheva, Sofiya Ivanovska
, Svetlozar Yordanov:
Grid Search Optimization of Novel SNN-ESN Classifier on a Supercomputer Platform. LSSC 2023: 435-443 - [c172]Nikola K. Kasabov:
Neuroinformatics, Neural Networks and Neurocomputers for Brain-inspired Computational Intelligence. SACI 2023: 13-14 - 2022
- [j184]Alexander Hui Xiang Yang, Nikola K. Kasabov, Yusuf Özgür Çakmak
:
Machine learning methods for the study of cybersickness: a systematic review. Brain Informatics 9(1): 24 (2022) - [j183]Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Alexander Merkin, Rita Krishnamurthi, Reza Enayatollahi, Valery Feigin, Nikola K. Kasabov:
Personalized Spiking Neural Network Models of Clinical and Environmental Factors to Predict Stroke. Cogn. Comput. 14(6): 2187-2202 (2022) - [j182]Peng Chen, Shihua Zhou
, Qiang Zhang
, Nikola K. Kasabov
:
A meta-inspired termite queen algorithm for global optimization and engineering design problems. Eng. Appl. Artif. Intell. 111: 104805 (2022) - [j181]Sensen Song, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
Salient detection via the fusion of background-based and multiscale frequency-domain features. Inf. Sci. 618: 53-71 (2022) - [j180]Dongdong Ni
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
A fast sand-dust video quality improvement method based on adaptive dynamic guided filtering and interframe detection strategy. J. Real Time Image Process. 19(6): 1181-1197 (2022) - [j179]Weijie Chen
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov:
Multispectral Image Enhancement Based on Weighted Principal Component Analysis and Improved Fractional Differential Mask. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j178]Enmei Tu, Zihao Wang, Jie Yang, Nikola K. Kasabov
:
Deep semi-supervised learning via dynamic anchor graph embedding in latent space. Neural Networks 146: 350-360 (2022) - [j177]Weijie Chen, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Multispectral Image Enhancement Based on the Dark Channel Prior and Bilateral Fractional Differential Model. Remote. Sens. 14(1): 233 (2022) - [j176]Lingli Guo
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Detail Preserving Low Illumination Image and Video Enhancement Algorithm Based on Dark Channel Prior. Sensors 22(1): 85 (2022) - [j175]Yong Liu, Miao Sun, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Denoising of Fluorescence Image on the Surface of Quantum Dot/Nanoporous Silicon Biosensors. Sensors 22(4): 1366 (2022) - [c171]Devarth Parikh, Yawen Lu, Nikola K. Kasabov, Guoyu Lu
:
Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives. IJCNN 2022: 1-8 - [c170]Iman Abouhassan, Nikola K. Kasabov, George Popov, Roumen Trifonov:
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. IS 2022: 1-7 - [p11]Zifei Wang, Xiaolin Huang, Jie Yang, Nikola K. Kasabov:
Universal Adversarial Perturbation Generated by Using Attention Information. Advances in Intelligent Systems Research and Innovation 2022: 21-39 - [i5]Aitor Martínez-Seras, Javier Del Ser, Jesus L. Lobo, Pablo García Bringas, Nikola K. Kasabov:
A Novel Explainable Out-of-Distribution Detection Approach for Spiking Neural Networks. CoRR abs/2210.00894 (2022) - 2021
- [j174]Aiwen Jia
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Single-Image Snow Removal Based on an Attention Mechanism and a Generative Adversarial Network. IEEE Access 9: 12852-12860 (2021) - [j173]Zhuang Huang
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
An Effective Algorithm for Specular Reflection Image Enhancement. IEEE Access 9: 154513-154523 (2021) - [j172]Shirin Dora
, Nikola K. Kasabov
:
Spiking Neural Networks for Computational Intelligence: An Overview. Big Data Cogn. Comput. 5(4): 67 (2021) - [j171]Urtats Etxegarai
, Eva Portillo
, Jon Irazusta
, Lucien Koefoed, Nikola K. Kasabov
:
A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners. Eur. J. Oper. Res. 291(2): 427-437 (2021) - [j170]Clarence Tan, Marko Sarlija
, Nikola K. Kasabov
:
NeuroSense: Short-term emotion recognition and understanding based on spiking neural network modelling of spatio-temporal EEG patterns. Neurocomputing 434: 137-148 (2021) - [j169]Maryam Gholami 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, Kristan Kang, Wei Wen, Valery Feigin, Nikola K. Kasabov:
Personalised predictive modelling with brain-inspired spiking neural networks of longitudinal MRI neuroimaging data and the case study of dementia. Neural Networks 144: 522-539 (2021) - [j168]Youxi He
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov:
Multispectral Image Change Detection Based on Single-Band Slow Feature Analysis. Remote. Sens. 13(15): 2969 (2021) - [j167]Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov
, Molood Barati, Grace Y. Wang
:
Deep Learning of Explainable EEG Patterns as Dynamic Spatiotemporal Clusters and Rules in a Brain-Inspired Spiking Neural Network. Sensors 21(14): 4900 (2021) - [j166]Yongji Li, Rui Wu, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Video Desnowing and Deraining via Saliency and Dual Adaptive Spatiotemporal Filtering. Sensors 21(22): 7610 (2021) - [c169]Wael Alzhrani, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov:
Emotion Recognition and Understanding Using EEG Data in A Brain-Inspired Spiking Neural Network Architecture. IJCNN 2021: 1-9 - [c168]Yawen Lu, Nikola K. Kasabov, Guoyu Lu
:
Multi-view Geometry Consistency Network for Facial Micro-Expression Recognition From Various Perspectives. IJCNN 2021: 1-8 - [e12]Mufti Mahmud
, M. Shamim Kaiser, Nikola K. Kasabov
, Khan Iftekharuddin
, Ning Zhong
:
Applied Intelligence and Informatics - First International Conference, AII 2021, Nottingham, UK, July 30-31, 2021, Proceedings. Communications in Computer and Information Science 1435, Springer 2021, ISBN 978-3-030-82268-2 [contents] - 2020
- [j165]Yaqiao Cheng
, Zhenhong Jia
, Huicheng Lai, Jie Yang
, Nikola K. Kasabov
:
Blue Channel and Fusion for Sandstorm Image Enhancement. IEEE Access 8: 66931-66940 (2020) - [j164]Yong Zhu
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Change Detection in Multitemporal Monitoring Images Under Low Illumination. IEEE Access 8: 126700-126712 (2020) - [j163]Bin Yang
, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Video Snow Removal Based on Self-Adaptation Snow Detection and Patch-Based Gaussian Mixture Model. IEEE Access 8: 160188-160201 (2020) - [j162]Junnan Wang
, Zhenhong Jia, Huicheng Lai
, Jie Yang
, Nikola K. Kasabov
:
A Multi-Information Fusion Correlation Filters Tracker. IEEE Access 8: 162022-162040 (2020) - [j161]Yaqiao Cheng
, Zhenhong Jia
, Huicheng Lai, Jie Yang
, Nikola K. Kasabov
:
A Fast Sand-Dust Image Enhancement Algorithm by Blue Channel Compensation and Guided Image Filtering. IEEE Access 8: 196690-196699 (2020) - [j160]Tengteng Zhang
, Sensen Song, Zhenhong Jia
, Jie Yang
, Nikola K. Kasabov
:
Object Motion Deblurring in Single Image Under Static Background. IEEE Access 8: 218069-218080 (2020) - [j159]Shihua Zhou
, Pinyan He, Nikola K. Kasabov
:
A Dynamic DNA Color Image Encryption Method Based on SHA-512. Entropy 22(10): 1091 (2020) - [j158]Elisa Capecci
, Jesus L. Lobo
, Ibai Laña
, Josafath Israel Espinosa Ramos, Nikola K. Kasabov
:
Modelling gene interaction networks from time-series gene expression data using evolving spiking neural networks. Evol. Syst. 11(4): 599-613 (2020) - [j157]Qinglai Wei
, Nikola K. Kasabov
, Marios M. Polycarpou, Zhigang Zeng:
Deep learning neural networks: Methods, systems, and applications. Neurocomputing 396: 130-132 (2020) - [j156]Zhi Li
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
An efficient and high quality medical CT image enhancement algorithm. Int. J. Imaging Syst. Technol. 30(4): 939-949 (2020) - [j155]Lanhua Zhang, Zhenhong Jia, Lucien Koefoed, Jie Yang, Nikola K. Kasabov
:
Remote sensing image enhancement based on the combination of adaptive nonlinear gain and the PLIP model in the NSST domain. Multim. Tools Appl. 79(19-20): 13647-13665 (2020) - [j154]Junhui Zuo, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Moving object detection in video sequence images based on an improved visual background extraction algorithm. Multim. Tools Appl. 79(39-40): 29663-29684 (2020) - [j153]Jesus L. Lobo
, Javier Del Ser
, Albert Bifet
, Nikola K. Kasabov
:
Spiking Neural Networks and online learning: An overview and perspectives. Neural Networks 121: 88-100 (2020) - [j152]Kaushalya Kumarasinghe, Nikola K. Kasabov
, Denise Taylor
:
Deep learning and deep knowledge representation in Spiking Neural Networks for Brain-Computer Interfaces. Neural Networks 121: 169-185 (2020) - [j151]Clarence Tan, Marko Sarlija
, Nikola K. Kasabov
:
Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture. Neural Process. Lett. 52(2): 1675-1701 (2020) - [j150]Anup Vanarse
, Josafath Israel Espinosa Ramos
, Adam Osseiran
, Alexander Rassau
, Nikola K. Kasabov
:
Application of a Brain-Inspired Spiking Neural Network Architecture to Odor Data Classification. Sensors 20(10): 2756 (2020) - [j149]Clarence Tan
, Gerardo Ceballos, Nikola K. Kasabov
, Narayan Puthanmadam Subramaniyam:
FusionSense: Emotion Classification Using Feature Fusion of Multimodal Data and Deep Learning in a Brain-Inspired Spiking Neural Network. Sensors 20(18): 5328 (2020) - [j148]Zohreh Gholami Doborjeh, Maryam Gholami 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
:
Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture. Sensors 20(24): 7354 (2020) - [j147]Balint Petro
, Nikola K. Kasabov
, Rita M. Kiss
:
Selection and Optimization of Temporal Spike Encoding Methods for Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 31(2): 358-370 (2020) - [j146]Ander Arriandiaga
, Eva Portillo
, Josafath Israel Espinosa Ramos
, Nikola K. Kasabov
:
Pulsewidth Modulation-Based Algorithm for Spike Phase Encoding and Decoding of Time-Dependent Analog Data. IEEE Trans. Neural Networks Learn. Syst. 31(10): 3920-3931 (2020) - [c167]Xuanlin He, Jie Yang, Nikola K. Kasabov
:
Application of an Improved Focal Loss in Vehicle Detection. ICAISC (1) 2020: 114-123 - [c166]Sugam Budhraja, Basabdatta Sen Bhattacharya
, Simon Durrant, Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola K. Kasabov
:
Sleep Stage Classification using NeuCube on SpiNNaker: a Preliminary Study. IJCNN 2020: 1-8 - [c165]Zifei Wang, Xiaolin Huang, Jie Yang, Nikola K. Kasabov
:
Universal Adversarial Perturbation Generated by Attacking Layer-wise Relevance Propagation. IEEE Conf. on Intelligent Systems 2020: 431-436 - [c164]Xiaoxu Liu, Wei Qi Yan, Nikola K. Kasabov
:
Vehicle-Related Scene Segmentation Using CapsNets. IVCNZ 2020: 1-6 - [c163]Norhanifah Murli, Nikola K. Kasabov
, Nurul Amirah Paham:
eSNN for Spatio-Temporal fMRI Brain Pattern Recognition with a Graphical Object Recognition Case Study. SCDM 2020: 470-478
2010 – 2019
- 2019
- [j145]Liyuan Ma
, Zhenhong Jia, Yinfeng Yu, Jie Yang, Nikola K. Kasabov
:
Multi-Spectral Image Change Detection Based on Band Selection and Single-Band Iterative Weighting. IEEE Access 7: 27948-27956 (2019) - [j144]Luyang Liu
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
SAR Image Change Detection Based on Mathematical Morphology and the K-Means Clustering Algorithm. IEEE Access 7: 43970-43978 (2019) - [j143]Ruyong Ren
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
, Xiaohui Huang
:
Quasi-Noise-Free and Detail-Preserved Digital Holographic Reconstruction. IEEE Access 7: 52155-52167 (2019) - [j142]Junhui Zuo
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Moving Target Detection Based on Improved Gaussian Mixture Background Subtraction in Video Images. IEEE Access 7: 152612-152623 (2019) - [j141]Piotr S. Maciag
, Nikola K. Kasabov
, Marzena Kryszkiewicz, Robert Bembenik
:
Air pollution prediction with clustering-based ensemble of evolving spiking neural networks and a case study for London area. Environ. Model. Softw. 118: 262-280 (2019) - [j140]Guo Qingrong
, Jia Zhenhong, Yang Jie, Nikola K. Kasabov
:
Contrast enhancement of medical images using fuzzy set theory and nonsubsampled shearlet transform. Int. J. Imaging Syst. Technol. 29(4): 483-490 (2019) - [j139]Liangliang Li, Linli Wang, Zhenhong Jia, Yujuan Si, Jie Yang, Nikola K. Kasabov:
A Practical Medical Image Enhancement Algorithm Based on Nonsubsampled Contourlet Transform. J. Medical Imaging Health Informatics 9(5): 1046-1056 (2019) - [j138]Liangliang Li, Linli Wang, Zuoxu Wang, Zhenhong Jia, Yujuan Si, Jie Yang, Nikola K. Kasabov:
A Novel Medical Image Fusion Approach Based on Nonsubsampled Shearlet Transform. J. Medical Imaging Health Informatics 9(9): 1815-1826 (2019) - [j137]Maryam Gholami Doborjeh, Nikola K. Kasabov
, Zohreh Gholami Doborjeh, Reza Enayatollahi, Enmei Tu, Amir H. Gandomi
:
Personalised modelling with spiking neural networks integrating temporal and static information. Neural Networks 119: 162-177 (2019) - [j136]Nikola K. Kasabov
:
Spiking neural networks for deep learning and knowledge representation: Editorial. Neural Networks 119: 341-342 (2019) - [j135]Xuemei Lou
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Change Detection in SAR Images Based on the ROF Model Semi-Implicit Denoising Method. Sensors 19(5): 1179 (2019) - [j134]Xiaoqian Yang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Change Detection of Optical Remote Sensing Image Disturbed by Thin Cloud Using Wavelet Coefficient Substitution Algorithm. Sensors 19(9): 1972 (2019) - [j133]Xuemei Lou
, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
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. Sensors 19(10): 2314 (2019) - [j132]Ruyong Ren, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Applying Speckle Noise Suppression to Refractive Indices Change Detection in Porous Silicon Microarrays. Sensors 19(13): 2975 (2019) - [j131]Josafath Israel Espinosa Ramos
, Elisa Capecci
, Nikola K. Kasabov
:
A Computational Model of Neuroreceptor-Dependent Plasticity (NRDP) Based on Spiking Neural Networks. IEEE Trans. Cogn. Dev. Syst. 11(1): 63-72 (2019) - [c162]Dhvani Shah, Grace Y. Wang
, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh, Nikola K. Kasabov
:
Deep Learning of EEG Data in the NeuCube Brain-Inspired Spiking Neural Network Architecture for a Better Understanding of Depression. ICONIP (3) 2019: 195-206 - [c161]Kaushalya Kumarasinghe, Denise Taylor
, Nikola K. Kasabov
:
eSPANNet: Evolving Spike Pattern Association Neural Network for Spike-based Supervised Incremental Learning and Its Application for Single-trial Brain Computer Interfaces. IJCNN 2019: 1-8 - [i4]Urtats Etxegarai, Eva Portillo, Jon Irazusta, Lucien Koefoed, Nikola K. Kasabov:
A heuristic approach for lactate threshold estimation for training decision-making: An accessible and easy to use solution for recreational runners. CoRR abs/1903.02318 (2019) - [i3]Jesus L. Lobo, Javier Del Ser, Albert Bifet, Nikola K. Kasabov:
Spiking Neural Networks and Online Learning: An Overview and Perspectives. CoRR abs/1908.08019 (2019) - 2018
- [j130]Xiaohui Huang
, Zhenhong Jia, Junlin Zhou, Jie Yang, Nikola K. Kasabov
:
Speckle Reduction of Reconstructions of Digital Holograms Using Gamma-Correction and Filtering. IEEE Access 6: 5227-5235 (2018) - [j129]Obada Al Zoubi
, Mariette Awad
, Nikola K. Kasabov
:
Anytime multipurpose emotion recognition from EEG data using a Liquid State Machine based framework. Artif. Intell. Medicine 86: 1-8 (2018) - [j128]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola K. Kasabov
:
Attentional Bias Pattern Recognition in Spiking Neural Networks from Spatio-Temporal EEG Data. Cogn. Comput. 10(1): 35-48 (2018) - [j127]Fahad Bashir Alvi, Russel Pears, Nikola K. Kasabov
:
An evolving spatio-temporal approach for gender and age group classification with Spiking Neural Networks. Evol. Syst. 9(2): 145-156 (2018) - [j126]Maryam Gholami Doborjeh, Nikola K. Kasabov
, Zohreh Gholami Doborjeh:
Evolving, dynamic clustering of spatio/spectro-temporal data in 3D spiking neural network models and a case study on EEG data. Evol. Syst. 9(3): 195-211 (2018) - [j125]Lukas Paulun, Anne Wendt
, Nikola K. Kasabov
:
A Retinotopic Spiking Neural Network System for Accurate Recognition of Moving Objects Using NeuCube and Dynamic Vision Sensors. Frontiers Comput. Neurosci. 12: 42 (2018) - [j124]Jesus L. Lobo
, Ibai Laña
, Javier Del Ser
, Miren Nekane Bilbao
, Nikola K. Kasabov
:
Evolving Spiking Neural Networks for online learning over drifting data streams. Neural Networks 108: 1-19 (2018) - [j123]Cheng Peng
, Fanghui Liu
, Jie Yang
, Nikola K. Kasabov
:
Densely Connected Discriminative Correlation Filters for Visual Tracking. IEEE Signal Process. Lett. 25(7): 1019-1023 (2018) - [j122]Cheng Peng
, Fanghui Liu
, Jie Yang
, Nikola K. Kasabov
:
Robust Visual Tracking via Dirac-Weighted Cascading Correlation Filters. IEEE Signal Process. Lett. 25(11): 1700-1704 (2018) - [j121]Neelava Sengupta
, Carolyn B. McNabb
, Nikola K. Kasabov
, Bruce Russell
:
Integrating Space, Time, and Orientation in Spiking Neural Networks: A Case Study on Multimodal Brain Data Modeling. IEEE Trans. Neural Networks Learn. Syst. 29(11): 5249-5263 (2018) - [c160]Nikola K. Kasabov:
Deep Learning in Spiking Neural Networks for Brain-Inspired Artificial Intelligence. CompSysTech 2018: 1 - [c159]Lu Wang
, Chao Ma, Enmei Tu, Jie Yang, Nikola K. Kasabov
:
Discrete Sparse Hashing for Cross-Modal Similarity Search. ICONIP (4) 2018: 256-267 - [c158]Mingjian Chen, Hao Zheng, Changsheng Lu, Enmei Tu, Jie Yang, Nikola K. Kasabov
:
A Spatio-Temporal Fully Convolutional Network for Breast Lesion Segmentation in DCE-MRI. ICONIP (7) 2018: 358-368 - [c157]Gautam Kishore Shahi
, Imanol Bilbao, Elisa Capecci, Durgesh Nandini, Maria Choukri, Nikola K. Kasabov
:
Analysis, Classification and Marker Discovery of Gene Expression Data with Evolving Spiking Neural Networks. ICONIP (5) 2018: 517-527 - [c156]Durgesh Nandini, Elisa Capecci, Lucien Koefoed, Ibai Laña
, Gautam Kishore Shahi
, Nikola K. Kasabov
:
Modelling and Analysis of Temporal Gene Expression Data Using Spiking Neural Networks. ICONIP (1) 2018: 571-581 - [c155]Jack Dray, Elisa Capecci, Nikola K. Kasabov
:
Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis. ICONIP (1) 2018: 625-634 - [c154]Kaushalya Kumarasinghe, Mahonri Owen
, Denise Taylor
, Nikola K. Kasabov
, Chi Kit:
FaNeuRobot: A Framework for Robot and Prosthetics Control Using the NeuCube Spiking Neural Network Architecture and Finite Automata Theory. ICRA 2018: 1-8 - [c153]Jesus L. Lobo
, Javier Del Ser
, Ibai Laña
, Miren Nekane Bilbao
, Nikola K. Kasabov
:
Drift Detection over Non-stationary Data Streams Using Evolving Spiking Neural Networks. IDC 2018: 82-94 - [c152]Ibai Laña
, Elisa Capecci, Javier Del Ser
, Jesus L. Lobo
, Nikola K. Kasabov
:
Road Traffic Forecasting Using NeuCube and Dynamic Evolving Spiking Neural Networks. IDC 2018: 192-203 - [c151]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola K. Kasabov
:
EEG Pattern Recognition using Brain-Inspired Spiking Neural Networks for Modelling Human Decision Processes. IJCNN 2018: 1-7 - [c150]Lucien Koefoed, Elisa Capecci, Nikola K. Kasabov
:
Analysis of Gene Expression Time Series Data of Ebola Vaccine response using the NeuCube and Temporal Feature Selection. IJCNN 2018: 1-7 - 2017
- [j120]Dayong Ren, Zhenhong Jia
, Jie Yang, Nikola K. Kasabov
:
A Practical GrabCut Color Image Segmentation Based on Bayes Classification and Simple Linear Iterative Clustering. IEEE Access 5: 18480-18487 (2017) - [j119]Chenjie Ge, Nikola K. Kasabov
, Zhi Liu
, Jie Yang:
A spiking neural network model for obstacle avoidance in simulated prosthetic vision. Inf. Sci. 399: 30-42 (2017) - [j118]Neelava Sengupta, Nikola K. Kasabov
:
Spike-time encoding as a data compression technique for pattern recognition of temporal data. Inf. Sci. 406: 133-145 (2017) - [j117]Apeng Zhou, Xizhong Qin, Zhenhong Jia, Nikola K. Kasabov:
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). 计算机科学 44(8): 64-70 (2017) - [j116]Pengyun Chen
, Yichen Zhang, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
Remote Sensing Image Change Detection Based on NSCT-HMT Model and Its Application. Sensors 17(6): 1295 (2017) - [j115]Zhiqing Guo, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
, Chuanxi Li:
Image Processing of Porous Silicon Microarray in Refractive Index Change Detection. Sensors 17(6): 1335 (2017) - [j114]Nikola K. Kasabov
, Lei Zhou, Maryam Gholami Doborjeh
, Zohreh Gholami Doborjeh, Jie Yang:
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. IEEE Trans. Cogn. Dev. Syst. 9(4): 293-303 (2017) - [j113]Nikola K. Kasabov
, Maryam Gholami Doborjeh, Zohreh Gholami Doborjeh:
Mapping, Learning, Visualization, Classification, and Understanding of fMRI Data in the NeuCube Evolving Spatiotemporal Data Machine of Spiking Neural Networks. IEEE Trans. Neural Networks Learn. Syst. 28(4): 887-899 (2017) - [j112]Enmei Tu, Nikola K. Kasabov
, Jie Yang:
Mapping Temporal Variables Into the NeuCube for Improved Pattern Recognition, Predictive Modeling, and Understanding of Stream Data. IEEE Trans. Neural Networks Learn. Syst. 28(6): 1305-1317 (2017) - [c149]Cheng Peng, Fanghui Liu, Haiyan Yang, Jie Yang, Nikola K. Kasabov
:
Correlation Filters with Adaptive Memories and Fusion for Visual Tracking. ICONIP (3) 2017: 170-179 - [c148]Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola K. Kasabov
:
Robust Kernel Approximation for Classification. ICONIP (1) 2017: 289-296 - [c147]Yuma Omori, Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola K. Kasabov
, Maryam Gholami Doborjeh:
EEG Comparison Between Normal and Developmental Disorder in Perception and Imitation of Facial Expressions with the NeuCube. ICONIP (4) 2017: 596-601 - 2016
- [j111]Tao Gao, Nikola K. Kasabov
:
Adaptive cow movement detection using evolving spiking neural network models. Evol. Syst. 7(4): 277-285 (2016) - [j110]Yu Cheng, Zhigang Jin, Tao Gao, Hongcai Chen, Nikola K. Kasabov
:
An improved collaborative representation based classification with regularized least square (CRC-RLS) method for robust face recognition. Neurocomputing 215: 250-259 (2016) - [j109]Enmei Tu, Yaqian Zhang
, Lin Zhu, Jie Yang, Nikola K. Kasabov
:
A graph-based semi-supervised k nearest-neighbor method for nonlinear manifold distributed data classification. Inf. Sci. 367-368: 673-688 (2016) - [j108]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, Fahad Bashir Alvi, Grace Y. Wang
, Denise Taylor
, Valery Feigin
, Sergei Gulyaev
, Mahmoud S. Mahmoud
, Zeng-Guang Hou, Jie Yang:
Evolving spatio-temporal data machines based on the NeuCube neuromorphic framework: Design methodology and selected applications. Neural Networks 78: 1-14 (2016) - [j107]Maryam Gholami Doborjeh, Grace Y. Wang
, Nikola K. Kasabov
, Robert Kydd, Bruce Russell
:
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. IEEE Trans. Biomed. Eng. 63(9): 1830-1841 (2016) - [j106]Hao Wu
, Lin Gao, Nikola K. Kasabov
:
Network-Based Method for Inferring Cancer Progression at the Pathway Level from Cross-Sectional Mutation Data. IEEE ACM Trans. Comput. Biol. Bioinform. 13(6): 1036-1044 (2016) - [j105]Pritam Bose
, Nikola K. Kasabov
, Lorenzo Bruzzone, Reggio N. Hartono:
Spiking Neural Networks for Crop Yield Estimation Based on Spatiotemporal Analysis of Image Time Series. IEEE Trans. Geosci. Remote. Sens. 54(11): 6563-6573 (2016) - [c146]Vivienne Breen, Nikola K. Kasabov
, Peng Du, Stefan Calder:
A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG). ANNPR 2016: 18-25 - [c145]Amit Soni Arya
, Vadlamani Ravi, Vadali Tejasviram, Neelava Sengupta, Nikola K. Kasabov
:
Cyber fraud detection using evolving spiking neural network. ICIIS 2016: 263-268 - [c144]Hideaki Kawano, Akinori Seo, Zohreh Gholami Doborjeh, Nikola K. Kasabov
, Maryam Gholami Doborjeh:
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. ICONIP (4) 2016: 221-227 - [c143]Zohreh Gholami Doborjeh, Maryam Gholami Doborjeh, Nikola K. Kasabov
:
Efficient Recognition of Attentional Bias Using EEG Data and the NeuCube Evolving Spatio-Temporal Data Machine. ICONIP (4) 2016: 645-653 - [c142]Elisa Capecci
, Zohreh Gholami Doborjeh, Nadia Mammone, Fabio La Foresta, Francesco Carlo Morabito
, Nikola K. Kasabov
:
Longitudinal study of alzheimer's disease degeneration through EEG data analysis with a NeuCube spiking neural network model. IJCNN 2016: 1360-1366 - [c141]Anne Abbott, Neelava Sengupta, Nikola K. Kasabov
:
Which method to use for optimal structure and function representation of large spiking neural networks: A case study on the NeuCube architecture. IJCNN 2016: 1367-1372 - [c140]Maryam Gholami Doborjeh, Nikola K. Kasabov
:
Personalised modelling on integrated clinical and EEG Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network system. IJCNN 2016: 1373-1378 - [c139]Nikola K. Kasabov
, Neelava Sengupta, Nathan Matthew Scott:
From von neumann, John Atanasoff and ABC to Neuromorphic computation and the NeuCube spatio-temporal data machine. IEEE Conf. on Intelligent Systems 2016: 15-21 - [i2]Enmei Tu, Nikola K. Kasabov, Jie Yang:
Mapping Temporal Variables into the NeuCube for Improved Pattern Recognition, Predictive Modelling and Understanding of Stream Data. CoRR abs/1603.05594 (2016) - [i1]Enmei Tu, Yaqian Zhang, Lin Zhu, Jie Yang, Nikola K. Kasabov:
A Graph-Based Semi-Supervised k Nearest-Neighbor Method for Nonlinear Manifold Distributed Data Classification. CoRR abs/1606.00985 (2016) - 2015
- [j104]Hao Wu
, Lin Gao, Feng Li, Fei Song, Xiaofei Yang
, Nikola K. Kasabov
:
Identifying overlapping mutated driver pathways by constructing gene networks in cancer. BMC Bioinform. 16(S-5): S3 (2015) - [j103]Wen Liang, Yingjie Hu, Nikola K. Kasabov
:
Evolving personalized modeling system for integrated feature, neighborhood and parameter optimization utilizing gravitational search algorithm. Evol. Syst. 6(1): 1-14 (2015) - [j102]Enmei Tu, Jie Yang, Nikola K. Kasabov
, Yaqian Zhang
:
Posterior Distribution Learning (PDL): A novel supervised learning framework using unlabeled samples to improve classification performance. Neurocomputing 157: 173-186 (2015) - [j101]Jing-jing Wang, Zhenhong Jia, Xizhong Qin, Jie Yang, Nikola K. Kasabov
:
Medical image enhancement algorithm based on NSCT and the improved fuzzy contrast. Int. J. Imaging Syst. Technol. 25(1): 7-14 (2015) - [j100]Lu Liu, Zhenhong Jia, Jie Yang, Nikola K. Kasabov
:
A medical image enhancement method using adaptive thresholding in NSCT domain combined unsharp masking. Int. J. Imaging Syst. Technol. 25(3): 199-205 (2015) - [j99]Nikola K. Kasabov
, Elisa Capecci
:
Spiking neural network methodology for modelling, classification and understanding of EEG spatio-temporal data measuring cognitive processes. Inf. Sci. 294: 565-575 (2015) - [j98]Tao Gao, Nikola K. Kasabov
:
A method used for Dotted Data Matrix image processing. J. Comput. Methods Sci. Eng. 15(4): 685-693 (2015) - [j97]Nikola K. Kasabov
:
Evolving connectionist systems for adaptive learning and knowledge discovery: Trends and directions. Knowl. Based Syst. 80: 24-33 (2015) - [j96]Elisa Capecci
, Nikola K. Kasabov
, Grace Y. Wang
:
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. Neural Networks 68: 62-77 (2015) - [c138]Maryam Gholami Doborjeh, Nikola K. Kasabov
:
Dynamic 3D Clustering of Spatio-Temporal Brain Data in the NeuCube Spiking Neural Network Architecture on a Case Study of fMRI Data. ICONIP (4) 2015: 191-198 - [c137]Yu Zhao, Yu Qiao, Jie Yang, Nikola K. Kasabov
:
Abnormal Activity Detection Using Spatio-Temporal Feature and Laplacian Sparse Representation. ICONIP (4) 2015: 410-418 - [c136]Shaoyong Jia, Yuding Liang, Xianyang Chen, Yun Gu, Jie Yang, Nikola K. Kasabov
, Yu Qiao:
Adaptive Location for Multiple Salient Objects Detection. ICONIP (3) 2015: 411-418 - [c135]Liangdong Li, Nikola K. Kasabov
, Jie Yang, Lixiu Yao, Zhenghong Jia:
Poisson Image Denoising Based on BLS-GSM Method. ICONIP (4) 2015: 513-522 - [c134]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
:
Modelling Absence Epilepsy seizure data in the NeuCube evolving spiking neural network architecture. IJCNN 2015: 1-8 - [c133]Long Peng, Zeng-Guang Hou, Nikola K. Kasabov
, Jin Hu, Liang Peng, Weiqun Wang:
sEMG-based torque estimation for robot-assisted lower limb rehabilitation. IJCNN 2015: 1-5 - [p10]Nikola K. Kasabov
:
Evolving Connectionist Systems: From Neuro-Fuzzy-, to Spiking- and Neuro-Genetic. Handbook of Computational Intelligence 2015: 771-782 - [p9]Elisa Capecci
, Francesco Carlo Morabito
, Maurizio Campolo
, Nadia Mammone, Domenico Labate, Nikola K. Kasabov
:
A Feasibility Study of Using the NeuCube Spiking Neural Network Architecture for Modelling Alzheimer's Disease EEG Data. Advances in Neural Networks 2015: 159-172 - [e11]Plamen Angelov
, Krassimir T. Atanassov, Lyubka Doukovska, Mincho Hadjiski, Vladimir Simov Jotsov, Janusz Kacprzyk, Nikola K. Kasabov, Sotir Sotirov, Eulalia Szmidt, Slawomir Zadrozny
:
Intelligent Systems'2014 - Proceedings of the 7th International Conference Intelligent Systems IEEE IS'2014, September 24-26, 2014, Warsaw, Poland, Volume 1: Mathematical Foundations, Theory, Analyses. Advances in Intelligent Systems and Computing 322, Springer 2015, ISBN 978-3-319-11312-8 [contents] - 2014
- [j95]Xin Yi, Yingjie Hu, Zhenhong Jia, Liejun Wang, Jie Yang, Nikola K. Kasabov
:
An enhanced multiphase Chan-Vese model for the remote sensing image segmentation. Concurr. Comput. Pract. Exp. 26(18): 2893-2906 (2014) - [j94]Nikola K. Kasabov
, Valery Feigin
, Zeng-Guang Hou, Yixiong Chen, Linda Liang, Rita Krishnamurthi, Muhaini Othman
, Priya Parmar
:
Evolving spiking neural networks for personalised modelling, classification and prediction of spatio-temporal patterns with a case study on stroke. Neurocomputing 134: 269-279 (2014) - [j93]Enmei Tu, Longbing Cao
, Jie Yang, Nikola K. Kasabov
:
A novel graph-based k-means for nonlinear manifold clustering and representative selection. Neurocomputing 143: 109-122 (2014) - [j92]Nikola K. Kasabov
:
NeuCube: A spiking neural network architecture for mapping, learning and understanding of spatio-temporal brain data. Neural Networks 52: 62-76 (2014) - [c132]Jin Hu, Zeng-Guang Hou, Yixiong Chen, Nikola K. Kasabov, Nathan Matthew Scott:
EEG-based classification of upper-limb ADL using SNN for active robotic rehabilitation. BioRob 2014: 409-414 - [c131]Maryam Gholami Doborjeh, Elisa Capecci
, Nikola K. Kasabov
:
Classification and segmentation of fMRI Spatio-Temporal Brain Data with a NeuCube evolving Spiking Neural Network model. EALS 2014: 73-80 - [c130]Wei Zhang, Jie Yang, Wenjing Jia
, Nikola K. Kasabov, Zhenhong Jia, Lei Zhou:
Unsupervised Segmentation Using Cluster Ensembles. ICONIP (3) 2014: 76-84 - [c129]Enmei Tu, Jie Yang, Zhenghong Jia, Nikola K. Kasabov:
Posterior Distribution Learning (PDL): A Novel Supervised Learning Framework. ICONIP (1) 2014: 86-94 - [c128]Norhanifah Murli, Nikola K. Kasabov, Bana Handaga
:
Classification of fMRI Data in the NeuCube Evolving Spiking Neural Network Architecture. ICONIP (1) 2014: 421-428 - [c127]Enmei Tu, Nikola K. Kasabov
, Muhaini Othman
, Yuxiao Li, Susan P. Worner, Jie Yang, Zhenghong Jia:
NeuCube(ST) for spatio-temporal data predictive modelling with a case study on ecological data. IJCNN 2014: 638-645 - [c126]Muhaini Othman
, Nikola K. Kasabov
, Enmei Tu, Valery Feigin
, Rita Krishnamurthi, Zheng-Guang Hou, Yixiong Chen, Jin Hu:
Improved predictive personalized modelling with the use of Spiking Neural Network system and a case study on stroke occurrences data. IJCNN 2014: 3197-3204 - [c125]Denise Taylor
, Nathan Matthew Scott, Nikola K. Kasabov
, Elisa Capecci
, Enmei Tu, Nicola Saywell, Yixiong Chen, Jin Hu, Zeng-Guang Hou:
Feasibility of NeuCube SNN architecture for detecting motor execution and motor intention for use in BCIapplications. IJCNN 2014: 3221-3225 - [c124]Reggio N. Hartono, Russel Pears, Nikola K. Kasabov
, Susan P. Worner:
Extracting temporal knowledge from time series: A case study in ecological data. IJCNN 2014: 4237-4243 - 2013
- [j91]Stefan Schliebs, Nikola K. Kasabov
:
Evolving spiking neural network - a survey. Evol. Syst. 4(2): 87-98 (2013) - [j90]Russel Pears, Harya Widiputra
, Nikola K. Kasabov
:
Evolving integrated multi-model framework for on line multiple time series prediction. Evol. Syst. 4(2): 99-117 (2013) - [j89]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola K. Kasabov
:
Training spiking neural networks to associate spatio-temporal input-output spike patterns. Neurocomputing 107: 3-10 (2013) - [j88]Ivan Jordanov
, Bruno Apolloni, Nikola K. Kasabov
:
Special Issue: Contemporary development of neural computation and applications. Neural Comput. Appl. 22(1): 1-2 (2013) - [c123]Nikola K. Kasabov:
The Evolution of the Evolving Neuro-Fuzzy Systems: From Expert Systems to Spiking-, Neurogenetic-, and Quantum Inspired. On Fuzziness (1) 2013: 271-280 - [c122]Stefan Schliebs, Nikola K. Kasabov
, Dave Parry, Doug Hunt
:
Towards a Wearable Coach: Classifying Sports Activities with Reservoir Computing. EANN (1) 2013: 233-242 - [c121]Stefan Schliebs, Elisa Capecci
, Nikola K. Kasabov
:
Spiking Neural Network for On-line Cognitive Activity Classification Based on EEG Data. ICONIP (3) 2013: 55-62 - [c120]Nikola K. Kasabov
, Jin Hu, Yixiong Chen, Nathan Matthew Scott, Yulia Turkova:
Spatio-temporal EEG Data Classification in the NeuCube 3D SNN Environment: Methodology and Examples. ICONIP (3) 2013: 63-69 - [c119]Yixiong Chen, Jin Hu, Nikola K. Kasabov
, Zeng-Guang Hou, Long Cheng:
NeuCubeRehab: A Pilot Study for EEG Classification in Rehabilitation Practice Based on Spiking Neural Networks. ICONIP (3) 2013: 70-77 - [c118]Nathan Matthew Scott, Nikola K. Kasabov
, Giacomo Indiveri
:
NeuCube Neuromorphic Framework for Spatio-temporal Brain Data and Its Python Implementation. ICONIP (3) 2013: 78-84 - [c117]Lei Zhou, Chen Gong, YiJun Li, Yu Qiao, Jie Yang, Nikola K. Kasabov
:
Salient Object Segmentation Based on Automatic Labeling. ICONIP (3) 2013: 584-591 - [e10]Valeri M. Mladenov, Petia D. Koprinkova-Hristova
, Günther Palm, Alessandro E. P. Villa
, Bruno Appollini, Nikola K. Kasabov:
Artificial Neural Networks and Machine Learning - ICANN 2013 - 23rd International Conference on Artificial Neural Networks, Sofia, Bulgaria, September 10-13, 2013. Proceedings. Lecture Notes in Computer Science 8131, Springer 2013, ISBN 978-3-642-40727-7 [contents] - 2012
- [j87]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola K. Kasabov
:
Span: Spike Pattern Association Neuron for Learning Spatio-Temporal Spike Patterns. Int. J. Neural Syst. 22(4) (2012) - [j86]Shaoning Pang
, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov
:
LDA Merging and Splitting With Applications to Multiagent Cooperative Learning and System Alteration. IEEE Trans. Syst. Man Cybern. Part B 42(2): 552-564 (2012) - [c116]Nikola K. Kasabov
:
NeuCube EvoSpike Architecture for Spatio-temporal Modelling and Pattern Recognition of Brain Signals. ANNPR 2012: 225-243 - [c115]Stefan Schliebs, Maurizio Fiasché
, Nikola K. Kasabov
:
Constructing Robust Liquid State Machines to Process Highly Variable Data Streams. ICANN (1) 2012: 604-611 - [c114]Ammar Mohemmed, Guoyu Lu
, Nikola K. Kasabov
:
Evaluating SPAN Incremental Learning for Handwritten Digit Recognition. ICONIP (3) 2012: 670-677 - [c113]Kshitij Dhoble, Nuttapod Nuntalid, Giacomo Indiveri
, Nikola K. Kasabov
:
Online spatio-temporal pattern recognition with evolving spiking neural networks utilising address event representation, rank order, and temporal spike learning. IJCNN 2012: 1-7 - [c112]Ammar Mohemmed, Nikola K. Kasabov
:
Incremental learning algorithm for spatio-temporal spike pattern classification. IJCNN 2012: 1-6 - [c111]Nikola K. Kasabov
:
Evolving spiking neural networks for spatio-and spectro-temporal pattern recognition. IEEE Conf. of Intelligent Systems 2012: 27-32 - [c110]Nikola K. Kasabov
:
Evolving Spiking Neural Networks and Neurogenetic Systems for Spatio- and Spectro-Temporal Data Modelling and Pattern Recognition. WCCI 2012: 234-260 - [e9]Plamen Angelov, Dimitar P. Filev, Nikola K. Kasabov, José Antonio Iglesias, Germán Gutiérrez:
2012 IEEE Conference on Evolving and Adaptive Intelligent Systems, EAIS 2012, Madrid, Spain, May 17-18, 2012. IEEE 2012, ISBN 978-1-4673-1727-6 [contents] - 2011
- [j85]Harya Widiputra
, Russel Pears, Nikola K. Kasabov
:
Dynamic Interaction Networks versus Local Trend Models for Multiple Time-Series Prediction. Cybern. Syst. 42(2): 100-123 (2011) - [j84]Shaoning Pang
, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov
:
Personalized mode transductive spanning SVM classification tree. Inf. Sci. 181(11): 2071-2085 (2011) - [j83]Shaoning Pang
, Lei Song, Nikola K. Kasabov
:
Correlation-aided support vector regression for forex time series prediction. Neural Comput. Appl. 20(8): 1193-1203 (2011) - [j82]Yaochu Jin
, Yan Meng, Juyang Weng, Nikola K. Kasabov
:
Guest Editorial Special Issue on Computational Modeling of Neural and Brain Development. IEEE Trans. Auton. Ment. Dev. 3(4): 273-275 (2011) - [j81]Nikola K. Kasabov
, Reinhard Schliebs, Hiroshi Kojima:
Probabilistic Computational Neurogenetic Modeling: From Cognitive Systems to Alzheimer's Disease. IEEE Trans. Auton. Ment. Dev. 3(4): 300-311 (2011) - [c109]Nikola K. Kasabov
, Stefan Schliebs, Ammar Mohemmed:
Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling. CIBB 2011: 1-9 - [c108]Wen Liang, Yingjie Hu, Nikola K. Kasabov
, Valery Feigin
:
Exploring Associations between Changes in Ambient Temperature and Stroke Occurrence: Comparative Analysis Using Global and Personalised Modelling Approaches. ICONIP (1) 2011: 129-137 - [c107]Stefan Schliebs, Haza Nuzly Abdull Hamed, Nikola K. Kasabov
:
Reservoir-Based Evolving Spiking Neural Network for Spatio-temporal Pattern Recognition. ICONIP (2) 2011: 160-168 - [c106]Nikola K. Kasabov
, Kshitij Dhoble, Nuttapod Nuntalid, Ammar Mohemmed:
Evolving Probabilistic Spiking Neural Networks for Spatio-temporal Pattern Recognition: A Preliminary Study on Moving Object Recognition. ICONIP (3) 2011: 230-239 - [c105]Nuttapod Nuntalid, Kshitij Dhoble, Nikola K. Kasabov
:
EEG Classification with BSA Spike Encoding Algorithm and Evolving Probabilistic Spiking Neural Network. ICONIP (1) 2011: 451-460 - [c104]Yingjie Hu, Nikola K. Kasabov
:
Personalised Modelling on SNPs Data for Crohn's Disease Prediction. ICONIP (1) 2011: 646-653 - [c103]Ammar Mohemmed, Stefan Schliebs, Nikola K. Kasabov
:
SPAN: A Neuron for Precise-Time Spike Pattern Association. ICONIP (2) 2011: 718-725 - [c102]Ammar Mohemmed, Stefan Schliebs, Satoshi Matsuda, Nikola K. Kasabov
:
Method for Training a Spiking Neuron to Associate Input-Output Spike Trains. EANN/AIAI (1) 2011: 219-228 - [c101]Haza Nuzly Abdull Hamed, Nikola K. Kasabov
, Siti Mariyam Shamsuddin, Harya Widiputra
, Kshitij Dhoble:
An extended Evolving Spiking Neural Network model for spatio-temporal pattern classification. IJCNN 2011: 2653-2656 - [c100]Ammar Mohemmed, Satoshi Matsuda, Stefan Schliebs, Kshitij Dhoble, Nikola K. Kasabov
:
Optimization of Spiking Neural Networks with dynamic synapses for spike sequence generation using PSO. IJCNN 2011: 2969-2974 - [c99]Stefan Schliebs, Ammar Mohemmed, Nikola K. Kasabov
:
Are probabilistic spiking neural networks suitable for reservoir computing? IJCNN 2011: 3156-3163 - [c98]Harya Widiputra, Russel Pears, Nikola K. Kasabov:
Multiple Time-Series Prediction through Multiple Time-Series Relationships Profiling and Clustered Recurring Trends. PAKDD (2) 2011: 161-172 - 2010
- [j80]Haza Nuzly Abdull Hamed, Nikola K. Kasabov, Siti Mariyam Shamsuddin:
Probabilistic Evolving Spiking Neural Network Optimization Using Dynamic Quantum-inspired Particle Swarm Optimization. Aust. J. Intell. Inf. Process. Syst. 11(1) (2010) - [j79]Maurizio Fiasché, Maria Cuzzola, Pasquale Iacopino, Nikola K. Kasabov, Francesco Carlo Morabito:
Personalized Modeling Based Gene Selection for Acute GvHD Gene Expression Data Analysis: A Computational Framework Proposed. Aust. J. Intell. Inf. Process. Syst. 12(4) (2010) - [j78]Plamen Angelov, Dimitar P. Filev, Nikola K. Kasabov:
Editorial. Evol. Syst. 1(1): 1-2 (2010) - [j77]Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Nikola K. Kasabov
:
Incremental linear discriminant analysis for evolving feature spaces in multitask pattern recognition problems. Evol. Syst. 1(1): 17-27 (2010) - [j76]Nikola K. Kasabov
, Yingjie Hu:
Integrated optimisation method for personalised modelling and case studies for medical decision support. Int. J. Funct. Informatics Pers. Medicine 3(3): 236-256 (2010) - [j75]Snjezana Soltic, Nikola K. Kasabov
:
Knowledge Extraction from Evolving Spiking Neural Networks with Rank Order Population Coding. Int. J. Neural Syst. 20(6): 437-445 (2010) - [j74]Stefan Schliebs, Nikola K. Kasabov
, Michael Defoin-Platel:
On the Probabilistic Optimization of Spiking Neural Networks. Int. J. Neural Syst. 20(6): 481-500 (2010) - [j73]Nikola K. Kasabov
:
To spike or not to spike: A probabilistic spiking neuron model. Neural Networks 23(1): 16-19 (2010) - [j72]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov
:
Evolving spiking neural networks for audiovisual information processing. Neural Networks 23(7): 819-835 (2010) - [c97]Nuwan Gunasekara
, Shaoning Pang
, Nikola K. Kasabov
:
Tuning N-gram String Kernel SVMs via Meta Learning. ICONIP (2) 2010: 91-98 - [c96]Stefan Schliebs, Nuttapod Nuntalid, Nikola K. Kasabov
:
Towards Spatio-Temporal Pattern Recognition Using Evolving Spiking Neural Networks. ICONIP (1) 2010: 163-170 - [c95]Ye Chen, Shaoning Pang
, Nikola K. Kasabov
:
Factorizing Class Characteristics via Group MEBs Construction. ICONIP (2) 2010: 283-290 - [c94]Shaoning Pang
, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov
:
Incremental and decremental LDA learning with applications. IJCNN 2010: 1-8 - [c93]Stefan Schliebs, Michael Defoin-Platel, Nikola K. Kasabov
:
Analyzing the dynamics of the simultaneous feature and parameter optimization of an evolving Spiking Neural Network. IJCNN 2010: 1-8 - [c92]Nikola K. Kasabov:
Evolving Integrative Brain-, Gene-, and Quantum Inspired Systems for Computational Intelligence and Knowledge Engineering. KES (1) 2010: 1 - [p8]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov:
Brain-Like Evolving Spiking Neural Networks for Multimodal Information Processing. Brain-Inspired Information Technology 2010: 15-27 - [p7]Naoki Shimo, Shaoning Pang, Keiichi Horio, Nikola K. Kasabov, Hakaru Tamukoh, Takanori Koga, Satoshi Sonoh, Hirohisa Isogai, Takeshi Yamakawa:
Effective and Adaptive Learning Based on Diversive/Specific Curiosity. Brain-Inspired Information Technology 2010: 171-175 - [p6]Nikola K. Kasabov
:
Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework. Advances in Machine Learning II 2010: 415-425
2000 – 2009
- 2009
- [j71]Anju Verma, Nikola K. Kasabov, Elaine Rush, Qun Song:
Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach. Aust. J. Intell. Inf. Process. Syst. 10(3) (2009) - [j70]Harya Widiputra, Russel Pears, Antoaneta Serguieva, Nikola K. Kasabov:
Dynamic interaction networks in modelling and predicting the behaviour of multiple interactive stock markets. Intell. Syst. Account. Finance Manag. 16(1-2): 189-205 (2009) - [j69]Shaoning Pang
, Nikola K. Kasabov
:
Encoding and decoding the knowledge of association rules over SVM classification trees. Knowl. Inf. Syst. 19(1): 79-105 (2009) - [j68]Nikola K. Kasabov
:
Integrative connectionist learning systems inspired by nature: current models, future trends and challenges. Nat. Comput. 8(2): 199-218 (2009) - [j67]Stefan Schliebs, Michael Defoin-Platel, Susan P. Worner, Nikola K. Kasabov
:
Integrated feature and parameter optimization for an evolving spiking neural network: Exploring heterogeneous probabilistic models. Neural Networks 22(5-6): 623-632 (2009) - [j66]Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov
:
Quantum-Inspired Evolutionary Algorithm: A Multimodel EDA. IEEE Trans. Evol. Comput. 13(6): 1218-1232 (2009) - [c91]Maurizio Fiasché
, Anju Verma, Maria Cuzzola
, Pasquale Iacopino, Nikola K. Kasabov
, Francesco Carlo Morabito
:
Discovering Diagnostic Gene Targets and Early Diagnosis of Acute GVHD Using Methods of Computational Intelligence over Gene Expression Data. ICANN (2) 2009: 10-19 - [c90]Shaoning Pang
, Tao Ban, Youki Kadobayashi, Nikola K. Kasabov
:
Spanning SVM Tree for Personalized Transductive Learning. ICANN (1) 2009: 913-922 - [c89]Harya Widiputra
, Henry Kho, Lukas
, Russel Pears, Nikola K. Kasabov
:
A Novel Evolving Clustering Algorithm with Polynomial Regression for Chaotic Time-Series Prediction. ICONIP (2) 2009: 114-121 - [c88]Anju Verma, Maurizio Fiasché
, Maria Cuzzola
, Pasquale Iacopino, Francesco Carlo Morabito
, Nikola K. Kasabov
:
Ontology Based Personalized Modeling for Type 2 Diabetes Risk Analysis: An Integrated Approach. ICONIP (2) 2009: 360-366 - [c87]Yingjie Hu, Nikola K. Kasabov
:
Coevolutionary Method for Gene Selection and Parameter Optimization in Microarray Data Analysis. ICONIP (2) 2009: 483-492 - [c86]Ye Chen, Shaoning Pang
, Nikola K. Kasabov
, Tao Ban, Youki Kadobayashi:
Hierarchical Core Vector Machines for Network Intrusion Detection. ICONIP (2) 2009: 520-529 - [c85]Zbynek Michlovský, Shaoning Pang
, Nikola K. Kasabov
, Tao Ban, Youki Kadobayashi:
String Kernel Based SVM for Internet Security Implementation. ICONIP (2) 2009: 530-539 - [c84]Haza Nuzly Abdull Hamed, Nikola K. Kasabov
, Zbynek Michlovský, Siti Mariyam Hj. Shamsuddin:
String Pattern Recognition Using Evolving Spiking Neural Networks and Quantum Inspired Particle Swarm Optimization. ICONIP (2) 2009: 611-619 - [c83]Seiichi Ozawa, Yuki Kawashima, Shaoning Pang
, Nikola K. Kasabov
:
Adaptive incremental principal component analysis in nonstationary online learning environments. IJCNN 2009: 2394-2400 - [c82]Shaoning Pang
, Seiichi Ozawa, Nikola K. Kasabov
:
Curiosity driven incremental LDA agent active learning. IJCNN 2009: 2401-2408 - [c81]Stefan Schliebs, Michael Defoin-Platel, Susan P. Worner, Nikola K. Kasabov
:
Quantum-inspired feature and parameter optimisation of evolving spiking neural networks with a case study from ecological modeling. IJCNN 2009: 2833-2840 - [c80]Haza Nuzly Abdull Hamed, Nikola K. Kasabov
, Siti Mariyam Shamsuddin:
Integrated Feature Selection and Parameter Optimization for Evolving Spiking Neural Networks Using Quantum Inspired Particle Swarm Optimization. SoCPaR 2009: 695-698 - [e8]Mario Köppen, Nikola K. Kasabov, George G. Coghill:
Advances in Neuro-Information Processing, 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part I. Lecture Notes in Computer Science 5506, Springer 2009, ISBN 978-3-642-02489-4 [contents] - [e7]Mario Köppen, Nikola K. Kasabov, George G. Coghill:
Advances in Neuro-Information Processing, 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II. Lecture Notes in Computer Science 5507, Springer 2009, ISBN 978-3-642-03039-0 [contents] - 2008
- [j65]Zeke S. H. Chan, Ilkka Havukkala
, Vishal Jain, Yingjie Hu, Nikola K. Kasabov
:
Soft computing methods to predict gene regulatory networks: An integrative approach on time-series gene expression data. Appl. Soft Comput. 8(3): 1189-1199 (2008) - [j64]Nikola K. Kasabov
:
Evolving Intelligence in Humans and Machines: Integrative Evolving Connectionist Systems Approach. IEEE Comput. Intell. Mag. 3(3): 23-37 (2008) - [j63]Nikola K. Kasabov
:
Adaptive modeling and discovery in bioinformatics: The evolving connectionist approach. Int. J. Intell. Syst. 23(5): 545-555 (2008) - [j62]Simei Gomes Wysoski, Lubica Benusková, Nikola K. Kasabov
:
Fast and adaptive network of spiking neurons for multi-view visual pattern recognition. Neurocomputing 71(13-15): 2563-2575 (2008) - [j61]Nikola K. Kasabov
, Vishal Jain, Lubica Benuskova:
Integrating evolving brain-gene ontology and connectionist-based system for modeling and knowledge discovery. Neural Networks 21(2-3): 266-275 (2008) - [j60]Plamen Angelov
, Dimitar P. Filev, Nikola K. Kasabov
:
Guest Editorial Evolving Fuzzy Systems - Preface to the Special Section. IEEE Trans. Fuzzy Syst. 16(6): 1390-1392 (2008) - [j59]Seiichi Ozawa, Shaoning Pang
, Nikola K. Kasabov
:
Incremental Learning of Chunk Data for Online Pattern Classification Systems. IEEE Trans. Neural Networks 19(6): 1061-1074 (2008) - [c79]Yuan-Chun Hwang, Qun Song, Nikola K. Kasabov
:
MUFIS: A neuro-fuzzy inference system using multiple types of fuzzy rules. FUZZ-IEEE 2008: 1411-1414 - [c78]Nikola K. Kasabov
:
Integrative Probabilistic Evolving Spiking Neural Networks Utilising Quantum Inspired Evolutionary Algorithm: A Computational Framework. ICONIP (1) 2008: 3-13 - [c77]Sean W. Gordon, Shaoning Pang
, Ryota Nishioka, Nikola K. Kasabov
, Takeshi Yamakawa:
Vision Based Mobile Robot for Indoor Environmental Security. ICONIP (1) 2008: 962-969 - [c76]Masayuki Hisada, Seiichi Ozawa, Kau Zhang, Shaoning Pang
, Nikola K. Kasabov
:
A Novel Incremental Linear Discriminant Analysis for Multitask Pattern Recognition Problems. ICONIP (1) 2008: 1163-1171 - [c75]Seiichi Ozawa, Kazuya Matsumoto, Shaoning Pang
, Nikola K. Kasabov
:
Incremental Principal Component Analysis Based on Adaptive Accumulation Ratio. ICONIP (1) 2008: 1196-1203 - [c74]Anju Verma, Nikola K. Kasabov
, Elaine Rush, Qun Song:
Ontology Based Personalized Modeling for Chronic Disease Risk Analysis: An Integrated Approach. ICONIP (1) 2008: 1204-1210 - [c73]Yingjie Hu, Qun Song, Nikola K. Kasabov
:
Personalized Modeling Based Gene Selection for Microarray Data Analysis. ICONIP (1) 2008: 1221-1228 - [c72]Stefan Schliebs, Michael Defoin-Platel, Nikola K. Kasabov
:
Integrated Feature and Parameter Optimization for an Evolving Spiking Neural Network. ICONIP (1) 2008: 1229-1236 - [c71]Harya Widiputra
, Russel Pears, Nikola K. Kasabov
:
Personalised Modelling for Multiple Time-Series Data Prediction: A Preliminary Investigation in Asia Pacific Stock Market Indexes Movement. ICONIP (1) 2008: 1237-1244 - [c70]Snjezana Soltic, Simei Gomes Wysoski, Nikola K. Kasabov
:
Evolving spiking neural networks for taste recognition. IJCNN 2008: 2091-2097 - [c69]Shaoning Pang
, Nikola K. Kasabov
:
r-SVMT: Discovering the knowledge of association rule over SVM classification trees. IJCNN 2008: 2486-2493 - [p5]Nikola K. Kasabov
, Qun Song, Lubica Benuskova, Paulo C. M. Gottgtroy, Vishal Jain, Anju Verma, Ilkka Havukkala
, Elaine Rush, Russel Pears, Alex Tjahjana, Yingjie Hu, Stephen G. MacDonell:
Integrating Local and Personalised Modelling with Global Ontology Knowledge Bases for Biomedical and Bioinformatics Decision Support. Computational Intelligence in Biomedicine and Bioinformatics 2008: 93-116 - [p4]Shaoning Pang
, Nikola K. Kasabov
:
SVMT-Rule: Association Rule Mining Over SVM Classification Trees. Rule Extraction from Support Vector Machines 2008: 135-162 - [p3]Nikola K. Kasabov
, Vishal Jain, Lubica Benuskova, Paulo C. M. Gottgtroy, Frances Joseph:
Integration of Brain-Gene Ontology and Simulation Systems for Learning, Modelling and Discovery. Computational Intelligence in Medical Informatics 2008: 221-234 - 2007
- [b1]Nikola K. Kasabov
:
Evolving connectionist systems - the knowledge engineering approach (2. ed.). Springer 2007, pp. I-XXI, 1-457 - [j58]Zeke S. H. Chan, Lesley Collins, Nikola K. Kasabov
:
Bayesian learning of sparse gene regulatory networks. Biosyst. 87(2-3): 299-306 (2007) - [j57]Nikola K. Kasabov
, Vishal Jain, Paulo C. M. Gottgtroy, Lubica Benuskova, Frances Joseph:
Brain Gene Ontology and Simulation System (bgos) for a Better Understanding of the Brain. Cybern. Syst. 38(5): 495-508 (2007) - [j56]Lubica Benuskova, Nikola K. Kasabov
:
Modeling L-LTP based on changes in concentration of pCREB transcription factor. Neurocomputing 70(10-12): 2035-2040 (2007) - [j55]Shaoning Pang
, Ilkka Havukkala
, Yingjie Hu, Nikola K. Kasabov
:
Classification consistency analysis for bootstrapping gene selection. Neural Comput. Appl. 16(6): 527-539 (2007) - [j54]Nikola K. Kasabov
:
Global, local and personalised modeling and pattern discovery in bioinformatics: An integrated approach. Pattern Recognit. Lett. 28(6): 673-685 (2007) - [c68]Michael Defoin-Platel, Stefan Schliebs, Nikola K. Kasabov
:
A versatile quantum-inspired evolutionary algorithm. IEEE Congress on Evolutionary Computation 2007: 423-430 - [c67]Nikola K. Kasabov:
Evolving Connectionist and Hybrid Systems: Methods, Tools, Applications. HIS 2007: 3 - [c66]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov:
Text-Independent Speaker Authentication with Spiking Neural Networks. ICANN (2) 2007: 758-767 - [c65]Seiichi Ozawa, Shaoning Pang
, Nikola K. Kasabov
:
Adaptive Face Recognition System Using Fast Incremental Principal Component Analysis. ICONIP (2) 2007: 396-405 - [c64]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov
:
Adaptive Spiking Neural Networks for Audiovisual Pattern Recognition. ICONIP (2) 2007: 406-415 - [c63]Boris Bacic, Nikola K. Kasabov
, Stephen G. MacDonell, Shaoning Pang
:
Evolving Connectionist Systems for Adaptive Sport Coaching. ICONIP (2) 2007: 416-425 - [c62]Yingjie Hu, Nikola K. Kasabov
:
Ontology-Based Framework for Personalized Diagnosis and Prognosis of Cancer Based on Gene Expression Data. ICONIP (2) 2007: 846-855 - [c61]Nikola K. Kasabov
, Vishal Jain, Paulo C. M. Gottgtroy, Lubica Benuskova, Simei Gomes Wysoski, Frances Joseph:
Evolving Brain-Gene Ontology System (EBGOS): Towards Integrating Bioinformatics and Neuroinformatics Data to Facilitate Discoveries. IJCNN 2007: 131-135 - [p2]Nikola K. Kasabov
:
Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities. Challenges for Computational Intelligence 2007: 193-219 - [e6]Andreas König, Mario Köppen, Nikola K. Kasabov, Ajith Abraham:
7th International Conference on Hybrid Intelligent Systems, HIS 2007, Kaiserslautern, Germany, September 17-19, 2007. IEEE Computer Society 2007, ISBN 0-7695-2946-1 [contents] - 2006
- [j53]Qun Song, Nikola K. Kasabov
, Tianmin Ma, Mark Roger Marshall
:
Integrating regression formulas and kernel functions into locally adaptive knowledge-based neural networks: A case study on renal function evaluation. Artif. Intell. Medicine 36(3): 235-244 (2006) - [j52]Nikola K. Kasabov
:
Adaptation and interaction in dynamical systems: Modelling and rule discovery through evolving connectionist systems. Appl. Soft Comput. 6(3): 307-322 (2006) - [j51]Zeke S. H. Chan, Nikola K. Kasabov
, Lesley Collins:
A two-stage methodology for gene regulatory network extraction from time-course gene expression data. Expert Syst. Appl. 30(1): 59-63 (2006) - [j50]Zeke S. H. Chan, Lesley Collins, Nikola K. Kasabov
:
An efficient greedy K-means algorithm for global gene trajectory clustering. Expert Syst. Appl. 30(1): 137-141 (2006) - [j49]Lubica Benuskova, Vishal Jain, Simei Gomes Wysoski, Nikola K. Kasabov
:
Computational Neurogenetic Modelling: a Pathway to New Discoveries in Genetic Neuroscience. Int. J. Neural Syst. 16(3): 215-226 (2006) - [j48]Zeke S. H. Chan, H. W. Ngan, Ahmad B. Rad, A. K. David, Nikola K. Kasabov
:
Short-term ANN load forecasting from limited data using generalization learning strategies. Neurocomputing 70(1-3): 409-419 (2006) - [j47]Seiichi Ozawa, Shaoning Pang, Nikola K. Kasabov:
Incremental learning of feature space and classifier for on-line pattern recognition. Int. J. Knowl. Based Intell. Eng. Syst. 10(1): 57-65 (2006) - [j46]Qun Song, Nikola K. Kasabov
:
TWNFI - a transductive neuro-fuzzy inference system with weighted data normalization for personalized modeling. Neural Networks 19(10): 1591-1596 (2006) - [c60]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov:
Adaptive Learning Procedure for a Network of Spiking Neurons and Visual Pattern Recognition. ACIVS 2006: 1133-1142 - [c59]Qun Song, Tianmin Ma, Nikola K. Kasabov:
TTLSC - Transductive Total Least Square Model for Classification and Its Application in Medicine. ADMA 2006: 197-204 - [c58]Seiichi Ozawa, Shaoning Pang
, Nikola K. Kasabov
:
An Incremental Principal Component Analysis for Chunk Data. FUZZ-IEEE 2006: 2278-2285 - [c57]Nikola K. Kasabov, Vishal Jain, Paulo C. M. Gottgtroy, Lubica Benuskova, Frances Joseph:
Brain-Gene Ontology: Integrating Bioinformatics and Neuroinformatics Data, Information and Knowledge to Enable Discoveries. HIS 2006: 13 - [c56]Simei Gomes Wysoski, Lubica Benuskova, Nikola K. Kasabov:
On-Line Learning with Structural Adaptation in a Network of Spiking Neurons for Visual Pattern Recognition. ICANN (1) 2006: 61-70 - [c55]Lubica Benuskova, Simei Gomes Wysoski, Nikola K. Kasabov:
Computational Neurogenetic Modeling: A Methodology to Study Gene Interactions Underlying Neural Oscillations. IJCNN 2006: 4638-4644 - [c54]Shaoning Pang
, Nikola K. Kasabov
:
Investigating LLE Eigenface on Pose and Face Identification. ISNN (2) 2006: 134-139 - [c53]Shaoning Pang
, Ilkka Havukkala
, Nikola K. Kasabov
:
Two-Class SVM Trees (2-SVMT) for Biomarker Data Analysis. ISNN (2) 2006: 629-634 - [c52]Ilkka Havukkala
, Lubica Benuskova, Shaoning Pang
, Vishal Jain, Rene Kroon, Nikola K. Kasabov:
Image and Fractal Information Processing for Large-Scale Chemoinformatics, Genomics Analyses and Pattern Discovery. PRIB 2006: 163-173 - [p1]Paulo C. M. Gottgtroy, Nikola K. Kasabov
, Stephen G. MacDonell:
Evolving ontologies for intelligent decision support. Fuzzy Logic and the Semantic Web 2006: 415-439 - [e5]Nikola K. Kasabov, Mario Köppen, Andreas König, Ajith Abraham, Qun Song:
6th International Conference on Hybrid Intelligent Systems (HIS 2006), 13-15 December 2006, Auckland, New Zealand. IEEE Computer Society 2006, ISBN 0-7695-2662-4 [contents] - 2005
- [j45]Nikola K. Kasabov, Hojjat Adeli, Nikhil R. Pal:
Introduction. Int. J. Neural Syst. 15(1-2) (2005) - [j44]Liang Goh, Nikola K. Kasabov
:
An Integrated Feature Selection and Classification Method to Select Minimum Number of Variables on the Case Study of Gene Expression Data. J. Bioinform. Comput. Biol. 3(5): 1107-1136 (2005) - [j43]Zeke S. H. Chan, Nikola K. Kasabov
, Lesley Collins:
A Hybrid Genetic Algorithm and Expectation Maximization Method for Global Gene Trajectory Clustering. J. Bioinform. Comput. Biol. 3(5): 1227-1242 (2005) - [j42]Seiichi Ozawa, Soon Lee Toh, Shigeo Abe
, Shaoning Pang
, Nikola K. Kasabov
:
Incremental learning of feature space and classifier for face recognition. Neural Networks 18(5-6): 575-584 (2005) - [j41]Zeke S. H. Chan, Nikola K. Kasabov
:
A Preliminary Study on Negative Correlation Learning via Correlation-Corrected Data (NCCD). Neural Process. Lett. 21(3): 207-214 (2005) - [j40]Qun Song, Nikola K. Kasabov
:
NFI: a neuro-fuzzy inference method for transductive reasoning. IEEE Trans. Fuzzy Syst. 13(6): 799-808 (2005) - [j39]Zeke S. H. Chan, Nikola K. Kasabov
:
Fast neural network ensemble learning via negative-correlation data correction. IEEE Trans. Neural Networks 16(6): 1707-1710 (2005) - [j38]Shaoning Pang
, Seiichi Ozawa, Nikola K. Kasabov
:
Incremental linear discriminant analysis for classification of data streams. IEEE Trans. Syst. Man Cybern. Part B 35(5): 905-914 (2005) - [c51]L. Huang, Qun Song, Nikola K. Kasabov
:
Evolving Connectionist Systems Based Role Allocation of Robots for Soccer Playing. ISIC 2005: 36-40 - [c50]Tianmin Ma, Qun Song, Nikola K. Kasabov, Mark Roger Marshall:
TWNFC - Transductive Neural-Fuzzy Classifier with Weighted Data Normalization and Its Application in Medicine. CIMCA/IAWTIC 2005: 479-484 - [c49]Qun Song, Tianmin Ma, Nikola K. Kasabov:
Transductive Knowledge Based Fuzzy Inference System for Personalized Modeling. FSKD (2) 2005: 528-535 - [c48]Nikola K. Kasabov, Lubica Benuskova, Simei Gomes Wysoski:
Computational Neurogenetic Modeling: Integration of Spiking Neural Networks, Gene Networks, and Signal Processing Techniques. ICANN (2) 2005: 509-514 - [c47]Shaoning Pang
, Seiichi Ozawa, Nikola K. Kasabov:
Chunk Incremental LDA Computing on Data Streams. ISNN (2) 2005: 51-56 - [c46]Nikola K. Kasabov:
Computational Intelligence for Bioinformatics: The Knowledge Engineering Approach. SGAI Conf. 2005: 3-4 - [c45]Zeke S. H. Chan, Nikola K. Kasabov:
Global EM Learning of Finite Mixture Models using the Greedy Elimination Method. SGAI Conf. 2005: 37-45 - [c44]Zeke S. H. Chan, Nikola K. Kasabov:
Fast Estimation of Distribution Algorithm (EDA) via Constrained Multi-Parent Recombination. SGAI Conf. 2005: 161-174 - [e4]Mike Barley, Nikola K. Kasabov:
Intelligent Agents and Multi-Agent Systems, 7th Pacific Rim International Workshop on Multi-Agents, PRIMA 2004, Auckland, New Zealand, August 8-13, 2004, Revised Selected Papers. Lecture Notes in Computer Science 3371, Springer 2005, ISBN 3-540-25340-8 [contents] - 2004
- [j37]Zeke S. H. Chan, Nikola K. Kasabov:
Evolutionary Computation For On-Line And Off-Line Parameter Tuning Of Evolving Fuzzy Neural Networksc. Int. J. Comput. Intell. Appl. 4(3): 309- (2004) - [j36]Nikola K. Kasabov, Shaoning Pang:
Editorial. Int. J. Comput. Syst. Signals 5(2): 1 (2004) - [j35]Akbar Ghobakhlou, Nikola K. Kasabov:
A Methodology and a System for Adaptive, Integrated Speech and Image Learning and Recognition. Int. J. Comput. Syst. Signals 5(2): 2-16 (2004) - [c43]Liang Goh, Qun Song, Nikola K. Kasabov:
A Novel Feature Selection Method to Improve Classification of Gene Expression Data. APBC 2004: 161-166 - [c42]Nikola K. Kasabov:
Discovering Rules of Adaptation and Interaction: From Molecules and Gene Interaction to Brain Functions. HIS 2004: 3 - [c41]David Zhang, Akbar Ghobakhlou, Nikola K. Kasabov:
An adaptive model of person identification combining speech and image information. ICARCV 2004: 413-418 - [c40]Shaoning Pang
, Seiichi Ozawa, Nikola K. Kasabov:
One-Pass Incremental Membership Authentication by Face Classification. ICBA 2004: 155-161 - [c39]Akbar Ghobakhlou, David Zhang, Nikola K. Kasabov:
An Evolving Neural Network Model for Person Verification Combining Speech and Image. ICONIP 2004: 381-386 - [c38]Qun Song, Nikola K. Kasabov:
TWRBF - Transductive RBF Neural Network with Weighted Data Normalization. ICONIP 2004: 633-640 - [c37]Snjezana Soltic, Shaoning Pang
, Nikola K. Kasabov, Susan P. Worner, Lora Peacock:
Dynamic Neuro-fuzzy Inference and Statistical Models for Risk Analysis of Pest Insect Establishment. ICONIP 2004: 971-976 - [c36]Nikola K. Kasabov, Zeke S. H. Chan, Vishal Jain, Igor Sidorov, Dimiter S. Dimitrov:
Gene Regulatory Network Discovery from Time-Series Gene Expression Data - A Computational Intelligence Approach. ICONIP 2004: 1344-1353 - [c35]Seiichi Ozawa, Shaoning Pang
, Nikola K. Kasabov:
A Modified Incremental Principal Component Analysis for On-Line Learning of Feature Space and Classifier. PRICAI 2004: 231-240 - [e3]Nikhil R. Pal, Nikola K. Kasabov, Rajani K. Mudi, Srimanta Pal, Swapan K. Parui:
Neural Information Processing, 11th International Conference, ICONIP 2004, Calcutta, India, November 22-25, 2004, Proceedings. Lecture Notes in Computer Science 3316, Springer 2004, ISBN 3-540-23931-6 [contents] - 2003
- [j34]Matthias E. Futschik
, Anthony Reeve, Nikola K. Kasabov
:
Evolving connectionist systems for knowledge discovery from gene expression data of cancer tissue. Artif. Intell. Medicine 28(2): 165-189 (2003) - [j33]Lorenzo Rizzi, Flavio Bazzana
, Nikola K. Kasabov
, Mario Fedrizzi, Luca Erzegovesi
:
Simulation of ECB decisions and forecast of short term Euro rate with an adaptive fuzzy expert system. Eur. J. Oper. Res. 145(2): 363-381 (2003) - [j32]Da Deng, Nikola K. Kasabov
:
On-line pattern analysis by evolving self-organizing maps. Neurocomputing 51: 87-103 (2003) - [j31]Nikola K. Kasabov
:
Spoken language analysis, modeling and recognition - Cstatistical and adaptive connectionist approaches. Inf. Sci. 156(1-2): 1-2 (2003) - [j30]Waleed H. Abdulla
, Nikola K. Kasabov
:
Reduced feature-set based parallel CHMM speech recognition systems. Inf. Sci. 156(1-2): 21-38 (2003) - [j29]Akbar Ghobakhlou, Michael J. Watts
, Nikola K. Kasabov
:
Adaptive speech recognition with evolving connectionist systems. Inf. Sci. 156(1-2): 71-83 (2003) - [j28]Mark R. Laws, Richard Kilgour, Nikola K. Kasabov
:
Modeling the emergence of bilingual acoustic clusters: a preliminary case study. Inf. Sci. 156(1-2): 85-107 (2003) - [c34]Nikola K. Kasabov, Melanie Middlemiss, T. Lane:
A Generic Connectionist-Based Method for On-Line Feature Selection and Modelling with a Case Study of Gene Expression Data Analysis. APBC 2003: 199-202 - 2002
- [j27]Nikola K. Kasabov
, Qun Song:
DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Trans. Fuzzy Syst. 10(2): 144-154 (2002) - [c33]Michael J. Watts
, Nikola K. Kasabov
:
Evolutionary optimisation of evolving connectionist systems. IEEE Congress on Evolutionary Computation 2002: 606-610 - [c32]Matthias E. Futschik
, Nikola K. Kasabov:
Fuzzy clustering of gene expression data. FUZZ-IEEE 2002: 414-419 - 2001
- [j26]Nikola K. Kasabov
:
On-line learning, reasoning, rule extraction and aggregation in locally optimized evolving fuzzy neural networks. Neurocomputing 41(1-4): 25-45 (2001) - [j25]Nikola K. Kasabov, Jaesoo Kim, Robert Kozma, Tico Cohen:
Rule Extraction from Fuzzy Neural Networks FuNN: A Method and a Real-World Application. J. Adv. Comput. Intell. Intell. Informatics 5(4): 193-200 (2001) - [j24]Nikola K. Kasabov
:
Evolving fuzzy neural networks for supervised/unsupervised online knowledge-based learning. IEEE Trans. Syst. Man Cybern. Part B 31(6): 902-918 (2001) - [c31]Michael J. Watts
, Nikola K. Kasabov:
Dynamic optimisation of evolving connectionist system training parameters by pseudo-evolution strategy. CEC 2001: 1335-1342 - [c30]Brendon J. Woodford, Nikola K. Kasabov:
Ensembles of EFuNNs: An Architecture for a Mutlimodule Classifier. FUZZ-IEEE 2001: 1573-1576 - [c29]Da Deng, Nikola K. Kasabov:
An evolving localised learning model for on-line image colour quantisation. ICIP (1) 2001: 906-909 - 2000
- [j23]Nikola K. Kasabov, Robert Kozma:
Methods and systems for intelligent human-computer interaction. Inf. Sci. 123(1-2): 1-2 (2000) - [j22]Nikola K. Kasabov
, Eric O. Postma, H. Jaap van den Herik:
AVIS: a connectionist-based framework for integrated auditory and visual information processing. Inf. Sci. 123(1-2): 127-148 (2000) - [j21]Nikola K. Kasabov, Steven A. Israel, Brendon J. Woodford:
The Application of Hybrid Evolving Connectionist Systems to Image Classification. J. Adv. Comput. Intell. Intell. Informatics 4(1): 57-65 (2000) - [c28]Irena Koprinska
, Nikola K. Kasabov
:
Evolving Fuzzy Neural Network for Camera Operations Recognition. ICPR 2000: 2523-2526 - [c27]Da Deng, Nikola K. Kasabov:
ESOM: An Algorithm to Evolve Self-Organizing Maps from On-Line Data Streams. IJCNN (6) 2000: 3-8 - [c26]Nikola K. Kasabov, Georgi Iliev
:
Hybrid System for Robust Recognition of Noisy Speech Based on Evolving Fuzzy Neural Networks and Adaptive Filtering. IJCNN (5) 2000: 91-96
1990 – 1999
- 1999
- [j20]Nikola K. Kasabov, Richard Kilgour, S. J. Sinclair:
From hybrid adjustable neuro-fuzzy systems to adaptive connectionist-based systems for phoneme and word recognition. Fuzzy Sets Syst. 103(2): 349-367 (1999) - [j19]Jaesoo Kim, Nikola K. Kasabov
:
HyFIS: adaptive neuro-fuzzy inference systems and their application to nonlinear dynamical systems. Neural Networks 12(9): 1301-1319 (1999) - [c25]Nikola K. Kasabov:
Evolving connectionist systems: A theory and a case study on adaptive speech recognition. IJCNN 1999: 3002-3007 - 1998
- [j18]Nikola K. Kasabov, Robert Kozma:
Introduction: Hybrid intelligent adaptive systems. Int. J. Intell. Syst. 13(6): 453-454 (1998) - [j17]Nikola K. Kasabov, Robert Kozma:
Hybrid intelligent adaptive systems: A framework and a case study on speech recognition. Int. J. Intell. Syst. 13(6): 455-466 (1998) - [j16]Robert Kozma, Nikola K. Kasabov, Jaesoo Kim, Tico Cohen:
Integration of connectionist methods and chaotic time-series analysis for the prediction of process data. Int. J. Intell. Syst. 13(6): 519-538 (1998) - [j15]Nikola K. Kasabov, Robert Kozma, Michael J. Watts:
Phoneme-Based Speech Recognition via Fuzzy Neural Networks Modeling and Learning. Inf. Sci. 110(1-2): 61-79 (1998) - [j14]Nikola K. Kasabov, Robert Kozma:
Editorial: Self-Organization and Adaptation in Intelligent Systems. J. Adv. Comput. Intell. Intell. Informatics 2(6): 177 (1998) - [j13]Nikola K. Kasabov:
The ECOS Framework and the ECO Learning Method for Evolving Connectionist Systems. J. Adv. Comput. Intell. Intell. Informatics 2(6): 195-202 (1998) - [c24]Nikola K. Kasabov:
Evolving Connectionist Systems and Evolving Brains. ICONIP 1998: 12-13 - [c23]Michael J. Watts, Nikola K. Kasabov:
Genetic Algorithms for the Design of Fuzzy Neural Networks. ICONIP 1998: 793-796 - [c22]Nikola K. Kasabov:
ECOS: Evolving Connectionist Systems and the ECO Learning Paradigm. ICONIP 1998: 1232-1235 - [c21]Eric O. Postma, Nikola K. Kasabov, H. Jaap van den Herik:
Enhancing recognition systems through an integrated processing of visual and audio information. SMC 1998: 1591-1596 - [e2]Nikola K. Kasabov, Robert Kozma, Kitty Ko, Robert O'Shea, George G. Coghill, Tom Gedeon:
Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, ICONIP 1997, Volume I, Dunedin, New Zealand, 24-28 November, 1997. Springer 1998, ISBN 0-444-88545-5 [contents] - [e1]Nikola K. Kasabov, Robert Kozma, Kitty Ko, Robert O'Shea, George G. Coghill, Tom Gedeon:
Progress in Connectionist-Based Information Systems: Proceedings of the 1997 International Conference on Neural Information Processing and Intelligent Information Systems, ICONIP 1997, Volume II, Dunedin, New Zealand, 24-28 November, 1997. Springer 1998 [contents] - 1997
- [j12]Nikola K. Kasabov
, Kaoru Hirota:
Special Issue on Advanced Neuro-Fuzzy Techniques and Their Applications: Introduction. Inf. Sci. 101(3-4): 153-154 (1997) - [j11]Nikola K. Kasabov, Jaesoo Kim, Michael J. Watts, Andrew R. Gray
:
FuNN/2 - A Fuzzy Neural Network Architecture for Adaptive Learning and Knowledge Acquisition. Inf. Sci. 101(3-4): 155-175 (1997) - [j10]Steven A. Israel, Nikola K. Kasabov:
Statistical, connectionist, and fuzzy inference techniques for image classification. J. Electronic Imaging 6(3): 337-347 (1997) - [j9]Nikola K. Kasabov:
Learning Strategies for Modular Neuro-Fuzzy Systems: A Case Study on Phoneme-Based Speech Recognition. J. Intell. Fuzzy Syst. 5(4): 345-354 (1997) - [c20]Nikola K. Kasabov:
Fuzzy rules extraction, reasoning and rules adaptation in fuzzy neural networks. ICNN 1997: 2380-2383 - [c19]Nikola K. Kasabov
, Michael J. Watts:
Genetic algorithms for structural optimisation, dynamic adaptation and automated design of fuzzy neural networks. ICNN 1997: 2546-2549 - [c18]Robert Kozma, J. A. Swope, Nikola K. Kasabov, M. J. A. Williams:
Multi-Agent Implementation of Fractal Analysis by Fuzzy Neural Networks. ICONIP (1) 1997: 162-165 - [c17]Alexander P. Topchy, Oleg A. Lebedko, Victor V. Miagkikh, Nikola K. Kasabov:
Adaptive Training of Radial Basis Function Networks Based on Cooperative Evolution and Evolutionary Programming. ICONIP (1) 1997: 253-258 - [c16]Jaesoo Kim, A. Mowat, P. Poole, Nikola K. Kasabov:
Neuro-Fuzzy and Multivariate Statistical Classification of Fruit Populations Based on Visible-Near Infrared Spectrophotometry Data. ICONIP (2) 1997: 780-784 - [c15]Quingqing Zhou, Martin K. Purvis, Nikola K. Kasabov:
A Membership Function Selection Method for Fuzzy Neural Networks. ICONIP (2) 1997: 785-788 - [c14]Nikola K. Kasabov, Robert Kozma, Richard Kilgour, Mark R. Laws, J. Taylor, Michael J. Watts, Andrew R. Gray:
A Methodology for Speech Data Analysis and a Framework for Adaptive Speech Recognition Using Fuzzy Neural Networks. ICONIP (2) 1997: 1055-1060 - [c13]Andrew R. Gray, Richard Kilgour, Nikola K. Kasabov:
An Agent Based Framework for Modular Speech Recognition and Language Processing Systems. ICONIP (2) 1997: 1076-1079 - 1996
- [j8]Nikola K. Kasabov, Takeshi Yamakawa:
Preface. Fuzzy Sets Syst. 82(2): 133 (1996) - [j7]Nikola K. Kasabov:
Learning fuzzy rules and approximate reasoning in fuzzy neural networks and hybrid systems. Fuzzy Sets Syst. 82(2): 135-149 (1996) - [j6]Nikola K. Kasabov
:
Adaptable neuro production systems. Neurocomputing 13(2-4): 95-117 (1996) - [j5]Nikola K. Kasabov:
Fril - Fuzzy and Evidential Reasoning in Artificial Intelligence, by J. F. Baldwin, T. P. Martin, and B. W. Pilsworth. J. Am. Soc. Inf. Sci. 47(10): 790-791 (1996) - 1995
- [j4]Nikola K. Kasabov
:
Hybrid Connectionist Fuzzy Production System: Towards Building Comprehensive AI. Intell. Autom. Soft Comput. 1(4): 355-364 (1995) - [j3]Nikola K. Kasabov
, Simon H. Lavington, S. Lin, C. Wang:
Model for exploiting associative matching in AI production systems. Knowl. Based Syst. 8(1): 14-20 (1995) - [c12]Max Bailey, Nikola K. Kasabov, Peter Mason, Andrew R. Gray
, Tico Cohen:
Hybrid Systems for Prediction - A Case Study of Predicting Effluent Flow to a Sewage Plant. ANNES 1995: 261-264 - [c11]Max Bailey, Clive Solomon, Nikola K. Kasabov, Simon Greig:
Hybrid Systems for Medical Data Analysis and Decision Making - A Case Study on Varicose Vein Disorders . ANNES 1995: 265-268 - [c10]Nikola K. Kasabov, S. J. Sinclair, Richard Kilgour, Catherine I. Watson
, Mark R. Laws, Diana Kassabova:
Intelligent human computer interfaces and the case study of building English-to-Maori talking dictionary. ANNES 1995: 294-297 - 1994
- [c9]Nikola K. Kasabov:
Hybrid Connectionist Fuzzy Systems for Speech Recognition and the Use of Connectionist Production Systems. IEEE/Nagoya-University World Wisepersons Workshop 1994: 19-33 - 1993
- [c8]Nikola K. Kasabov
, Daniel Nikovski, Emilian Peev:
Speech recognition based on Kohonen self-organizing feature maps and hybrid connectionist systems. ANNES 1993: 113-117 - [c7]Nikola K. Kasabov
:
Learning fuzzy rules through neural networks. ANNES 1993: 137-139 - [c6]Nikola K. Kasabov
, Lakhmi C. Jain:
Connectionist expert systems. ANNES 1993: 220-221 - [c5]Nikola K. Kasabov:
Connectionist Fuzzy Production Systems. Fuzzy Logic in Artificial Intelligence 1993: 114-128 - 1992
- [c4]Nikola K. Kasabov, Daniel Nikovski:
Prognostic Expert Systems on a Hybrid Connectionist Environment. AIMSA 1992: 141-148 - [c3]Nikola K. Kasabov, S. H. Petkov:
Neural Networks and Logic Programming - a Hybrid Model and its Applicability to Building Expert Systems. ECAI 1992: 287-288 - 1990
- [c2]Nikola K. Kasabov:
Hybrid Connectionist Rule-Based Systems. AIMSA 1990: 227-235
1980 – 1989
- 1985
- [j2]Nikola K. Kasabov
:
A method for SIMD/MIMD functionally reconfigurable multimicroprocessor systems design and parallel data exchange algorithms. Parallel Comput. 2(1): 73-78 (1985) - [j1]Nikola K. Kasabov
:
Functionally reconfigurable general purpose parallel machines and some image processing and pattern recognition applications. Pattern Recognit. Lett. 3(3): 215-223 (1985) - 1981
- [c1]Nikola K. Kasabov
, G. T. Bijev, B. J. Jechev:
Hierarchical discrete systems and realisation of parallel algorithms. CONPAR 1981: 414-422
Coauthor Index
aka: Lubica Benuskova
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