| ECA-Net: Efficient channel attention for deep convolutional neural networks Q Wang, B Wu, P Zhu, P Li, W Zuo, Q Hu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 7034 | 2020 |
| Neighborhood rough set based heterogeneous feature subset selection Q Hu, D Yu, J Liu, C Wu Information sciences 178 (18), 3577-3594, 2008 | 1135 | 2008 |
| Enhancing geometric factors in model learning and inference for object detection and instance segmentation Z Zheng, P Wang, D Ren, W Liu, R Ye, Q Hu, W Zuo IEEE transactions on cybernetics 52 (8), 8574-8586, 2021 | 1125 | 2021 |
| Progressive image deraining networks: A better and simpler baseline D Ren, W Zuo, Q Hu, P Zhu, D Meng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1025 | 2019 |
| Detection and tracking meet drones challenge P Zhu, L Wen, D Du, X Bian, H Fan, Q Hu, H Ling IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 7380 …, 2021 | 687 | 2021 |
| Generalized latent multi-view subspace clustering C Zhang, H Fu, Q Hu, X Cao, Y Xie, D Tao, D Xu IEEE transactions on pattern analysis and machine intelligence 42 (1), 86-99, 2018 | 660 | 2018 |
| Neighborhood classifiers Q Hu, D Yu, Z Xie Expert systems with applications 34 (2), 866-876, 2008 | 630 | 2008 |
| VisDrone-DET2019: The vision meets drone object detection in image challenge results D Du, P Zhu, L Wen, X Bian, H Lin, Q Hu, T Peng, J Zheng, X Wang, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 600 | 2019 |
| Latent multi-view subspace clustering C Zhang, Q Hu, H Fu, P Zhu, X Cao Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 600 | 2017 |
| Information-preserving hybrid data reduction based on fuzzy-rough techniques Q Hu, D Yu, Z Xie Pattern recognition letters 27 (5), 414-423, 2006 | 550 | 2006 |
| Vision meets drones: A challenge P Zhu, L Wen, X Bian, H Ling, Q Hu arXiv preprint arXiv:1804.07437, 2018 | 524 | 2018 |
| Transfer learning for short-term wind speed prediction with deep neural networks Q Hu, R Zhang, Y Zhou Renewable Energy 85, 83-95, 2016 | 504 | 2016 |
| Hybrid attribute reduction based on a novel fuzzy-rough model and information granulation Q Hu, Z Xie, D Yu Pattern recognition 40 (12), 3509-3521, 2007 | 485 | 2007 |
| A new approach to attribute reduction of consistent and inconsistent covering decision systems with covering rough sets C Degang, W Changzhong, H Qinghua Information Sciences 177 (17), 3500-3518, 2007 | 455 | 2007 |
| Neural blind deconvolution using deep priors D Ren, K Zhang, Q Wang, Q Hu, W Zuo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 345 | 2020 |
| Unsupervised feature selection by regularized self-representation P Zhu, W Zuo, L Zhang, Q Hu, SCK Shiu Pattern Recognition 48 (2), 438-446, 2015 | 343 | 2015 |
| Fuzzy probabilistic approximation spaces and their information measures Q Hu, D Yu, Z Xie, J Liu IEEE transactions on fuzzy systems 14 (2), 191-201, 2006 | 336 | 2006 |
| Mixed feature selection based on granulation and approximation Q Hu, J Liu, D Yu Knowledge-Based Systems 21 (4), 294-304, 2008 | 302 | 2008 |
| Selecting discrete and continuous features based on neighborhood decision error minimization Q Hu, W Pedrycz, D Yu, J Lang IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 40 …, 2009 | 290 | 2009 |
| Feature selection based on neighborhood discrimination index C Wang, Q Hu, X Wang, D Chen, Y Qian, Z Dong IEEE transactions on neural networks and learning systems 29 (7), 2986-2999, 2017 | 276 | 2017 |
Pengfei ZhuProfessor, College of Intelligence and Computing , Tianjin UniversityGeverifieerd e-mailadres voor tju.edu.cn
