| The devil is in the channels: Mutual-channel loss for fine-grained image classification D Chang, Y Ding, J Xie, AK Bhunia, X Li, Z Ma, M Wu, J Guo, YZ Song IEEE Transactions on Image Processing 29, 4683-4695, 2020 | 226 | 2020 |
| Fine-grained visual classification via progressive multi-granularity training of jigsaw patches R Du, D Chang, AK Bhunia, J Xie, Z Ma, YZ Song, J Guo In ECCV, 153-168, 2020 | 205 | 2020 |
| Prediction of short-term PV power output and uncertainty analysis L Liu, Y Zhao, D Chang, J Xie, Z Ma, Q Sun, H Yin, R Wennersten Applied energy 228, 700-711, 2018 | 171 | 2018 |
| Fine-grained vehicle classification with channel max pooling modified CNNs Z Ma, D Chang, J Xie, Y Ding, S Wen, X Li, Z Si, J Guo IEEE Transactions on Vehicular Technology 68 (4), 3224-3233, 2019 | 116 | 2019 |
| Dual cross-entropy loss for small-sample fine-grained vehicle classification X Li, L Yu, D Chang, Z Ma, J Cao IEEE Transactions on Vehicular Technology 68 (5), 4204-4212, 2019 | 109 | 2019 |
| AP-CNN: Weakly supervised attention pyramid convolutional neural network for fine-grained visual classification Y Ding, Z Ma, S Wen, J Xie, D Chang, Z Si, M Wu, H Ling IEEE Transactions on Image Processing 30, 2826-2836, 2021 | 99 | 2021 |
| Your "Flamingo" is My “Bird": Fine-Grained, or Not D Chang, K Pang, Y Zheng, Z Ma, YZ Song, J Guo In CVPP (Oral), 11476-11485, 2021 | 57 | 2021 |
| Softmax cross entropy loss with unbiased decision boundary for image classification J Cao, Z Su, L Yu, D Chang, X Li, Z Ma 2018 Chinese automation congress (CAC), 2028-2032, 2018 | 33 | 2018 |
| Progressive learning of category-consistent multi-granularity features for fine-grained visual classification R Du, J Xie, Z Ma, D Chang, YZ Song, J Guo IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9521 …, 2021 | 31 | 2021 |
| Oslnet: Deep small-sample classification with an orthogonal softmax layer X Li, D Chang, Z Ma, ZH Tan, JH Xue, J Cao, J Yu, J Guo IEEE Transactions on Image Processing 29, 6482-6495, 2020 | 27 | 2020 |
| Gpca: A probabilistic framework for gaussian process embedded channel attention J Xie, Z Ma, D Chang, G Zhang, J Guo IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8230 …, 2021 | 26 | 2021 |
| Progressive co-attention network for fine-grained visual classification T Zhang, D Chang, Z Ma, J Guo In VCIP, 1-5, 2021 | 21 | 2021 |
| Grad-CAM guided channel-spatial attention module for fine-grained visual classification S Xu, D Chang, J Xie, Z Ma 2021 IEEE 31st International Workshop on Machine Learning for Signal …, 2021 | 15 | 2021 |
| Deep InterBoost networks for small-sample image classification X Li, D Chang, Z Ma, ZH Tan, JH Xue, J Cao, J Guo Neurocomputing 456, 492-503, 2021 | 9 | 2021 |
| Iu-module: Intersection and union module for fine-grained visual classification Y Zheng, D Chang, J Xie, Z Ma 2020 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2020 | 8 | 2020 |
| Dual-attention guided dropblock module for weakly supervised object localization J Yin, S Zhang, D Chang, Z Ma, J Guo 2020 25th International Conference on Pattern Recognition (ICPR), 4229-4236, 2021 | 6 | 2021 |
| Competing ratio loss for discriminative multi-class image classification K Zhang, Y Guo, X Wang, D Chang, Z Zhao, Z Ma, TX Han Neurocomputing 464, 473-484, 2021 | 5 | 2021 |
| Fine-grained visual classification via simultaneously learning of multi-regional multi-grained features D Chang, Y Zheng, Z Ma, R Du, K Liang arXiv preprint arXiv:2102.00367, 2021 | 4 | 2021 |
| CC-Loss: Channel Correlation Loss for Image Classification Z Song, D Chang, Z Ma, X Li, ZH Tan 2020 25th International Conference on Pattern Recognition (ICPR), 7601-7608, 2021 | 3 | 2021 |
| Mind the gap: Enlarging the domain gap in open set domain adaptation D Chang, A Sain, Z Ma, YZ Song, J Guo arXiv preprint arXiv:2003.03787, 2020 | 3 | 2020 |
Zhanyu MaBeijing University of Posts and TelecommunicationsVerified email at bupt.edu.cn
