5 citations · 9 across the 8 of their papers we have counts for
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cs.CV2022
AugRmixAT: A Data Processing and Training Method for Improving Multiple Robustness and Generalization Performance
Xiaoliang Liu, Furao Shen, Jian Zhao +1
Deep neural networks are powerful, but they also have shortcomings such as their sensitivity to adversarial examples, noise, blur, occlusion, etc. Moreover, ensuring the reliabilit…
cs.CV2022★ 4 cited
RSTAM: An Effective Black-Box Impersonation Attack on Face Recognition using a Mobile and Compact Printer
Xiaoliang Liu, Furao Shen, Jian Zhao +1
Face recognition has achieved considerable progress in recent years thanks to the development of deep neural networks, but it has recently been discovered that deep neural networks…
cs.CV2022
RandoMix: A mixed sample data augmentation method with multiple mixed modes
Xiaoliang Liu, Furao Shen, Jian Zhao +1
Data augmentation plays a crucial role in enhancing the robustness and performance of machine learning models across various domains. In this study, we introduce a novel mixed-samp…