| Towards evaluating the robustness of deep diagnostic models by adversarial attack M Xu, T Zhang, Z Li, M Liu, D Zhang Medical Image Analysis 69, 101977, 2021 | 49 | 2021 |
| Medrdf: a robust and retrain-less diagnostic framework for medical pretrained models against adversarial attack M Xu, T Zhang, D Zhang IEEE Transactions on Medical Imaging 41 (8), 2130-2143, 2022 | 18 | 2022 |
| Infoat: Improving adversarial training using the information bottleneck principle M Xu, T Zhang, Z Li, D Zhang IEEE Transactions on Neural Networks and Learning Systems 35 (1), 1255-1264, 2022 | 12 | 2022 |
| Region-Based Dense Adversarial Generation for Medical Image Segmentation A Shen, L Sun, M Xu, D Zhang CAAI International Conference on Artificial Intelligence, 107-118, 2022 | 1 | 2022 |
| Scale-invariant adversarial attack for evaluating and enhancing adversarial defenses M Xu, T Zhang, Z Li, D Zhang arXiv preprint arXiv:2201.12527, 2022 | 1 | 2022 |
| A Consistency Regularization for Certified Robust Neural Networks M Xu, T Zhang, Z Li, D Zhang CAAI International Conference on Artificial Intelligence, 27-38, 2021 | 1 | 2021 |
| Improving the Certified Robustness of Neural Networks via Consistency Regularization M Xu, T Zhang, Z Li, D Zhang arXiv preprint arXiv:2012.13103, 2020 | | 2020 |
Daoqiang ZhangNanjing University of Aeronautics and Astronautics在 nuaa.edu.cn 的电子邮件经过验证
Daoqiang ZhangNanjing University of Aeronautics and Astronautics在 nuaa.edu.cn 的电子邮件经过验证