| ThiNet: A filter level pruning method for deep neural network compression JH Luo, J Wu, W Lin IEEE International Conference on Computer Vision (ICCV), 5058-5066, 2017 | 2330 | 2017 |
| Selective convolutional descriptor aggregation for fine-grained image retrieval XS Wei, JH Luo, J Wu, ZH Zhou IEEE transactions on image processing 26 (6), 2868-2881, 2017 | 504 | 2017 |
| Thinet: pruning cnn filters for a thinner net JH Luo, H Zhang, HY Zhou, CW Xie, J Wu, W Lin IEEE transactions on pattern analysis and machine intelligence 41 (10), 2525 …, 2019 | 291 | 2019 |
| Autopruner: An end-to-end trainable filter pruning method for efficient deep model inference JH Luo, J Wu Pattern Recognition 107, 107461, 2020 | 248 | 2020 |
| An entropy-based pruning method for cnn compression JH Luo, J Wu arXiv preprint arXiv:1706.05791, 2017 | 239 | 2017 |
| Neural network pruning with residual-connections and limited-data JH Luo, J Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 152 | 2020 |
| In defense of fully connected layers in visual representation transfer CL Zhang, JH Luo, XS Wei, J Wu Pacific Rim Conference on Multimedia, 807-817, 2017 | 110 | 2017 |
| 基于深度卷积特征的细粒度图像分类研究综述 罗建豪， 吴建鑫 自动化学报 43 (8), 1306-1318, 2017 | 70 | 2017 |
| Resource-constrained deep learning: challenges and practices JX Wu, BB Gao, XS Wei, JH Luo Sci Sin Inform 48, 501-510, 2018 | 9 | 2018 |
| Image categorization with resource constraints: introduction, challenges and advances JH Luo, W Zhou, J Wu Frontiers of Computer Science 11, 13-26, 2017 | 4 | 2017 |
| Dense CNN learning with equivalent mappings J Wu, CW Xie, JH Luo arXiv preprint arXiv:1605.07251, 2016 | 3 | 2016 |
| Learning effective binary visual representations with deep networks J Wu, JH Luo arXiv preprint arXiv:1803.03004, 2018 | 1 | 2018 |
Jianxin Wu (吴建鑫)Nanjing UniversityEmail verificata su nju.edu.cn
