| Constructing the L2-graph for robust subspace learning and subspace clustering X Peng, Z Yu, Z Yi, H Tang IEEE transactions on cybernetics 47 (4), 1053-1066, 2016 | 229 | 2016 |
| Feedforward categorization on AER motion events using cortex-like features in a spiking neural network B Zhao, R Ding, S Chen, B Linares-Barranco, H Tang IEEE transactions on neural networks and learning systems 26 (9), 1963-1978, 2014 | 205 | 2014 |
| Precise-spike-driven synaptic plasticity: Learning hetero-association of spatiotemporal spike patterns Q Yu, H Tang, KC Tan, H Li Plos one 8 (11), e78318, 2013 | 169 | 2013 |
| Connections between nuclear-norm and frobenius-norm-based representations X Peng, C Lu, Z Yi, H Tang IEEE transactions on neural networks and learning systems 29 (1), 218-224, 2016 | 166 | 2016 |
| Neural networks: computational models and applications H Tang, KC Tan, Z Yi Springer Science & Business Media, 2007 | 166 | 2007 |
| Rapid feedforward computation by temporal encoding and learning with spiking neurons Q Yu, H Tang, KC Tan, H Li IEEE transactions on neural networks and learning systems 24 (10), 1539-1552, 2013 | 151 | 2013 |
| Event-based neuromorphic vision for autonomous driving: A paradigm shift for bio-inspired visual sensing and perception G Chen, H Cao, J Conradt, H Tang, F Rohrbein, A Knoll IEEE Signal Processing Magazine 37 (4), 34-49, 2020 | 150 | 2020 |
| A unified framework for representation-based subspace clustering of out-of-sample and large-scale data X Peng, H Tang, L Zhang, Z Yi, S Xiao IEEE transactions on neural networks and learning systems 27 (12), 2499-2512, 2015 | 141 | 2015 |
| Spiking deep residual networks Y Hu, H Tang, G Pan IEEE Transactions on Neural Networks and Learning Systems, 2021 | 121 | 2021 |
| Robust subspace clustering via thresholding ridge regression X Peng, Z Yi, H Tang Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 119 | 2015 |
| A brain-inspired spiking neural network model with temporal encoding and learning Q Yu, H Tang, KC Tan, H Yu Neurocomputing 138, 3-13, 2014 | 116 | 2014 |
| A spiking neural network system for robust sequence recognition Q Yu, R Yan, H Tang, KC Tan, H Li IEEE transactions on neural networks and learning systems 27 (3), 621-635, 2015 | 81 | 2015 |
| A spike-timing-based integrated model for pattern recognition J Hu, H Tang, KC Tan, H Li, L Shi Neural computation 25 (2), 450-472, 2013 | 81 | 2013 |
| Adaptive memetic computing for evolutionary multiobjective optimization VA Shim, KC Tan, H Tang IEEE transactions on cybernetics 45 (4), 610-621, 2014 | 72 | 2014 |
| Temporal coding of local spectrogram features for robust sound recognition J Dennis, Q Yu, H Tang, HD Tran, H Li Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International …, 2013 | 66 | 2013 |
| On parameter settings of Hopfield networks applied to traveling salesman problems KC Tan, H Tang, SS Ge IEEE Transactions on Circuits and Systems I: Regular Papers 52 (5), 994-1002, 2005 | 65 | 2005 |
| Neural networks based approach for computing eigenvectors and eigenvalues of symmetric matrix Z Yi, Y Fu, HJ Tang Computers & Mathematics with Applications 47 (8-9), 1155-1164, 2004 | 64 | 2004 |
| How the brain formulates memory: A spatio-temporal model research frontier J Hu, H Tang, KC Tan, H Li IEEE Computational Intelligence Magazine 11 (2), 56-68, 2016 | 62 | 2016 |
| Bag of events: An efficient probability-based feature extraction method for AER image sensors X Peng, B Zhao, R Yan, H Tang, Z Yi IEEE transactions on neural networks and learning systems 28 (4), 791-803, 2016 | 58 | 2016 |
| Csnn: an augmented spiking based framework with perceptron-inception. Q Xu, Y Qi, H Yu, J Shen, H Tang, G Pan IJCAI, 1646-1652, 2018 | 57 | 2018 |
Professor Kay Chen TANChair Professor, Department of Computing, Hong Kong Polytechnic UniversityVerifisert e-postadresse på polyu.edu.hk
