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ORCIDNikola 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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Books and Theses
- 2007
[b1]Nikola K. Kasabov
:
Evolving connectionist systems - the knowledge engineering approach (2. ed.). Springer 2007, pp. I-XXI, 1-457
Journal Articles
- 2024
- [j204]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) - [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 P. 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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 P. 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) - 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) - 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 P. 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) - 2007
- [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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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) - 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)
Conference and Workshop Papers
- 2023
- [c174]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 - [c173]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 - [c172]Nikola K. Kasabov:
Neuroinformatics, Neural Networks and Neurocomputers for Brain-inspired Computational Intelligence. SACI 2023: 13-14 - 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 - 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 - 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 - 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 - 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
- [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
- [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 - 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 - 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
- [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 - 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 - 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
- [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 - 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 - 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 - 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 - 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 - 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 - 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 - 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
- [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
- [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
- [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 - 1999
- [c25]Nikola K. Kasabov:
Evolving connectionist systems: A theory and a case study on adaptive speech recognition. IJCNN 1999: 3002-3007 - 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 - 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 - 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 - 1981
- [c1]Nikola K. Kasabov, G. T. Bijev, B. J. Jechev:
Hierarchical discrete systems and realisation of parallel algorithms. CONPAR 1981: 414-422
Parts in Books or Collections
- 2022
- [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 - 2015
- [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 - 2010
- [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 - 2008
- [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
- [p2]Nikola K. Kasabov:
Brain-, Gene-, and Quantum Inspired Computational Intelligence: Challenges and Opportunities. Challenges for Computational Intelligence 2007: 193-219 - 2006
- [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
Editorship
- 2021
- [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] - 2015
- [e11]Plamen P. 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] - 2013
- [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
- [e9]Plamen P. 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] - 2009
- [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] - 2007
- [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
- [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
- [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
- [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] - 1998
- [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]
Informal and Other Publications
- 2022
- [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) - 2019
- [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) - 2016
- [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)
Coauthor Index
Lubica Benusková
aka: Lubica Benuskova
aka: Lubica Benuskova
[j204] [j203] [j202] [j195] [j194] [j193] [j192] [j190] [j188] [j187] [j181] [j180] [j179] [j177] [j176] [j175] [j174] [j173] [j168] [j166] [j165] [j164] [j163] [j162] [j161] [j160] [j156] [j155] [j154] [j145] [j144] [j143] [j142] [j139] [j138] [j135] [j134] [j133] [j132] [j130] [j120] [j117] [j116] [j115] [j101] [j100] [j95] [c130]
[j204] [j202] [j196] [j195] [j193] [j192] [j191] [j190] [j188] [j187] [j186] [j181] [j180] [j179] [j178] [j177] [j176] [j175] [j174] [j173] [j168] [j166] [j165] [j164] [j163] [j162] [j161] [j160] [j156] [j155] [j154] [j145] [j144] [j143] [j142] [j139] [j138] [j135] [j134] [j133] [j132] [j130] [j123] [j122] [j120] [j119] [j116] [j115] [j114] [j112] [j109] [j108] [j102] [j101] [j100] [j95] [j93] [c167] [c165] [c159] [c158] [c149] [c148] [c137] [c136] [c135] [c130] [c129] [c127] [c117] [p11] [i2] [i1]
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