| Transductive semi-supervised deep learning using min-max features W Shi, Y Gong, C Ding, ZMX Tao, N Zheng European Conference on Computer Vision (ECCV), 311-327, 2018 | 284 | 2018 |
| Multi-target multi-camera tracking by tracklet-to-target assignment Y He, X Wei, X Hong, W Shi, Y Gong IEEE Transactions on Image Processing 29, 5191-5205, 2020 | 114 | 2020 |
| JAMSNet: A remote pulse extraction network based on joint attention and multi-scale fusion C Zhao, H Wang, H Chen, W Shi, Y Feng IEEE Transactions on Circuits and Systems for Video Technology 33 (6), 2783-2797, 2022 | 74 | 2022 |
| Deep feature learning via structured graph Laplacian embedding for person re-identification D Cheng, Y Gong, X Chang, W Shi, A Hauptmann, N Zheng Pattern Recognition 82, 94-104, 2018 | 63 | 2018 |
| Fine-grained image classification using modified DCNNs trained by cascaded softmax and generalized large-margin losses W Shi, Y Gong, X Tao, D Cheng, N Zheng IEEE transactions on neural networks and learning systems 30 (3), 683-694, 2019 | 60 | 2019 |
| Training DCNN by combining max-margin, max-correlation objectives, and correntropy loss for multilabel image classification W Shi, Y Gong, X Tao, N Zheng IEEE transactions on neural networks and learning systems 29 (7), 2896-2908, 2018 | 46 | 2018 |
| Improving CNN performance accuracies with min–max objective W Shi, Y Gong, X Tao, J Wang, N Zheng IEEE transactions on neural networks and learning systems 29 (7), 2872-2885, 2018 | 45 | 2018 |
| Improving the performance of multisubject motor imagery-based BCIs using twin cascaded softmax CNNs J Luo, W Shi, N Lu, J Wang, H Chen, Y Wang, X Lu, X Wang, X Hei Journal of Neural Engineering 18 (3), 036024, 2021 | 28 | 2021 |
| Semantic knowledge guided class-incremental learning S Wang, W Shi, S Dong, X Gao, X Song, Y Gong IEEE Transactions on Circuits and Systems for Video Technology 33 (10), 5921 …, 2023 | 24 | 2023 |
| Object detection with class aware region proposal network and focused attention objective X Tao, Y Gong, W Shi, D Cheng Pattern Recognition Letters 130, 353-361, 2020 | 23 | 2020 |
| Consistency-Preserving deep hashing for fast person re-identification D Li, Y Gong, D Cheng, W Shi, X Tao, X Chang Pattern Recognition 94, 207-217, 2019 | 19 | 2019 |
| Improving CNN Performance with Min-Max Objective. W Shi, Y Gong, J Wang IJCAI, 2004-2010, 2016 | 19 | 2016 |
| Entropy and orthogonality based deep discriminative feature learning for object recognition W Shi, Y Gong, D Cheng, X Tao, N Zheng Pattern Recognition 81, 71-80, 2018 | 17 | 2018 |
| Transductive semisupervised deep hashing W Shi, Y Gong, B Chen, X Hei IEEE Transactions on Neural Networks and Learning Systems 33 (8), 3713-3726, 2022 | 16 | 2022 |
| Person re-identification by the asymmetric triplet and identification loss function D Cheng, Y Gong, W Shi, S Zhang Multimedia Tools and Applications 77 (3), 3533-3550, 2018 | 15 | 2018 |
| WITHDRAWN: Cross-scenario transfer metric learning for person re-identification D Cheng, Y Gong, Z Li, D Zhang, W Shi, X Zhang Pattern Recognition Letters, 2018 | 11 | 2018 |
| Directional methanolysis of kitchen waste for the co-production of methyl levulinate and fatty acid methyl esters: Catalytic strategy and machine learning modeling L Zhang, X Xing, Y Liu, W Shi, M Wang Bioresource Technology 367, 128274, 2023 | 10 | 2023 |
| Normalized non-negative sparse encoder for fast image representation S Zhang, J Wang, W Shi, Y Gong, Y Xia, Y Zhang IEEE Transactions on Circuits and Systems for Video Technology 29 (7), 1962-1972, 2019 | 9 | 2019 |
| Integrating supervised Laplacian objective with CNN for object recognition W Shi, Y Gong, J Wang, N Zheng Advances in Multimedia Information Processing-PCM 2016: 17th Pacific-Rim …, 2016 | 9 | 2016 |
| Unsupervised Monocular Estimation of Depth and Visual Odometry uUsing Attention and Depth-Pose Consistency Loss X Song, H Hu, L Liang, W Shi, G Xie, X Lu, X Hei IEEE Transactions on Multimedia, 2023 | 8 | 2023 |
