| Deep high-resolution representation learning for visual recognition J Wang, K Sun, T Cheng, B Jiang, C Deng, Y Zhao, D Liu, Y Mu, M Tan, ... IEEE transactions on pattern analysis and machine intelligence 43 (10), 3349 …, 2020 | 3590 | 2020 |
| Discrimination-aware channel pruning for deep neural networks Z Zhuang, M Tan, B Zhuang, J Liu, Y Guo, Q Wu, J Huang, J Zhu Advances in neural information processing systems 31, 2018 | 718 | 2018 |
| Graph convolutional networks for temporal action localization R Zeng, W Huang, M Tan, Y Rong, P Zhao, J Huang, C Gan Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 563 | 2019 |
| Domain-symmetric networks for adversarial domain adaptation Y Zhang, H Tang, K Jia, M Tan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 407 | 2019 |
| Closed-loop matters: Dual regression networks for single image super-resolution Y Guo, J Chen, J Wang, Q Chen, J Cao, Z Deng, Y Xu, M Tan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 387 | 2020 |
| Dense regression network for video grounding R Zeng, H Xu, W Huang, P Chen, M Tan, C Gan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 277 | 2020 |
| Towards effective low-bitwidth convolutional neural networks B Zhuang, C Shen, M Tan, L Liu, I Reid Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 277 | 2018 |
| Learning sparse svm for feature selection on very high dimensional datasets M Tan, L Wang, IW Tsang Proceedings of the 27th international conference on machine learning (ICML …, 2010 | 220 | 2010 |
| Visual grounding via accumulated attention C Deng, Q Wu, Q Wu, F Hu, F Lyu, M Tan Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 219 | 2018 |
| Efficient test-time model adaptation without forgetting S Niu, J Wu, Y Zhang, Y Chen, S Zheng, P Zhao, M Tan International conference on machine learning, 16888-16905, 2022 | 218 | 2022 |
| Attention guided network for retinal image segmentation S Zhang, H Fu, Y Yan, Y Zhang, Q Wu, M Yang, M Tan, Y Xu Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 217 | 2019 |
| Gene selection using hybrid particle swarm optimization and genetic algorithm S Li, X Wu, M Tan Soft Computing 12, 1039-1048, 2008 | 198 | 2008 |
| Towards ultrahigh dimensional feature selection for big data M Tan, IW Tsang, L Wang | 191 | 2014 |
| Heterogeneous domain adaptation for multiple classes JT Zhou, IW Tsang, SJ Pan, M Tan Artificial intelligence and statistics, 1095-1103, 2014 | 189 | 2014 |
| Location-aware graph convolutional networks for video question answering D Huang, P Chen, R Zeng, Q Du, M Tan, C Gan Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 11021 …, 2020 | 184 | 2020 |
| Structured binary neural networks for accurate image classification and semantic segmentation B Zhuang, C Shen, M Tan, L Liu, I Reid Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 176 | 2019 |
| Robust kernel low-rank representation S Xiao, M Tan, D Xu, ZY Dong IEEE transactions on neural networks and learning systems 27 (11), 2268-2281, 2015 | 176 | 2015 |
| Towards stable test-time adaptation in dynamic wild world S Niu, J Wu, Y Zhang, Z Wen, Y Chen, P Zhao, M Tan arXiv preprint arXiv:2302.12400, 2023 | 167 | 2023 |
| T-C3D: Temporal convolutional 3D network for real-time action recognition K Liu, W Liu, C Gan, M Tan, H Ma Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 158 | 2018 |
| Collaborative unsupervised domain adaptation for medical image diagnosis Y Zhang, Y Wei, Q Wu, P Zhao, S Niu, J Huang, M Tan IEEE Transactions on Image Processing 29, 7834-7844, 2020 | 152 | 2020 |
Ivor W. Tsang, IEEE FellowInaugural A*STAR AI Fellow and Director, Centre for Frontier AI Research, A*STARVerified email at cfar.a-star.edu.sg
