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ORCIDNikola K. Kasabov
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- 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
- 2021
[j168]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)- [j167]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) - [j166]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) - 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 Liu, 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) - [c163]Xuanlin He, Jie Yang, Nikola K. Kasabov:
Application of an Improved Focal Loss in Vehicle Detection. ICAISC (1) 2020: 114-123 - [c162]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 - [c161]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 - [c160]Xiaoxu Liu, Wei Qi Yan, Nikola K. Kasabov:
Vehicle-Related Scene Segmentation Using CapsNets. IVCNZ 2020: 1-6 - [c159]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) - [c158]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 - [c157]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) - [c156]Nikola K. Kasabov:
Deep Learning in Spiking Neural Networks for Brain-Inspired Artificial Intelligence. CompSysTech 2018: 1 - [c155]Lu Wang, Chao Ma, Enmei Tu, Jie Yang, Nikola K. Kasabov:
Discrete Sparse Hashing for Cross-Modal Similarity Search. ICONIP (4) 2018: 256-267 - [c154]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 - [c153]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 - [c152]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 - [c151]Jack Dray, Elisa Capecci, Nikola K. Kasabov:
Spiking Neural Networks for Cancer Gene Expression Time Series Modelling and Analysis. ICONIP (1) 2018: 625-634 - [c150]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 - [c149]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 - [c148]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 - [c147]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 - [c146]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) - [c145]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 - [c144]Fanghui Liu, Xiaolin Huang, Cheng Peng, Jie Yang, Nikola K. Kasabov:
Robust Kernel Approximation for Classification. ICONIP (1) 2017: 289-296 - [c143]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) - [c142]Vivienne Breen, Nikola K. Kasabov, Peng Du, Stefan Calder:
A Spiking Neural Network for Personalised Modelling of Electrogastrography (EGG). ANNPR 2016: 18-25 - [c141]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 - [c140]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 - [c139]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 - [c138]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 - [c137]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 - [c136]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) - [c135]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 - [c134]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 - [c133]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 - [c132]Liangdong Li, Nikola K. Kasabov, Jie Yang, Lixiu Yao, Zhenghong Jia:
Poisson Image Denoising Based on BLS-GSM Method. ICONIP (4) 2015: 513-522 - [c131]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 - [c130]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]