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2020 – today
- 2024
[j1]Ningping Mou, Binqing Guo, Lingchen Zhao, Cong Wang, Yue Zhao, Qian Wang:
No-Box Universal Adversarial Perturbations Against Image Classifiers via Artificial Textures. IEEE Trans. Inf. Forensics Secur. 19: 9803-9818 (2024)- [c6]Xinli Yue, Ningping Mou, Qian Wang, Lingchen Zhao:
Revisiting Adversarial Training Under Long-Tailed Distributions. CVPR 2024: 24492-24501 - [c5]Yunjie Ge, Pinji Chen, Qian Wang, Lingchen Zhao, Ningping Mou, Peipei Jiang, Cong Wang, Qi Li, Chao Shen:
More Simplicity for Trainers, More Opportunity for Attackers: Black-Box Attacks on Speaker Recognition Systems by Inferring Feature Extractor. USENIX Security Symposium 2024 - [i1]Xinli Yue, Ningping Mou, Qian Wang, Lingchen Zhao:
Revisiting Adversarial Training under Long-Tailed Distributions. CoRR abs/2403.10073 (2024) - 2023
- [c4]Yi Zhao, Ningping Mou
, Yunjie Ge, Qian Wang:
Improving Adversarial Transferability with Ghost Samples. ECAI 2023: 3107-3114 - [c3]Xinli Yue, Ningping Mou, Qian Wang, Lingchen Zhao:
Revisiting Adversarial Robustness Distillation from the Perspective of Robust Fairness. NeurIPS 2023 - 2022
- [c2]Yike Zhan, Baolin Zheng, Qian Wang, Ningping Mou, Binqing Guo, Qi Li, Chao Shen, Cong Wang:
Towards Black-Box Adversarial Attacks on Interpretable Deep Learning Systems. ICME 2022: 1-6 - [c1]Ningping Mou, Baolin Zheng, Qian Wang, Yunjie Ge, Binqing Guo:
A Few Seconds Can Change Everything: Fast Decision-based Attacks against DNNs. IJCAI 2022: 3342-3350
Coauthor Index
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