5 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CV2024★ 2 cited
Revisiting Adversarial Training under Long-Tailed Distributions
Xinli Yue, Ningping Mou, Qian Wang +1
Deep neural networks are vulnerable to adversarial attacks, often leading to erroneous outputs. Adversarial training has been recognized as one of the most effective methods to cou…
cs.CR2024
Hijacking Attacks against Neural Networks by Analyzing Training Data
Yunjie Ge, Qian Wang, Huayang Huang +7
Backdoors and adversarial examples are the two primary threats currently faced by deep neural networks (DNNs). Both attacks attempt to hijack the model behaviors with unintended ou…
cs.CV2023★ 5 cited
Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition
JiaCheng Deng, Li Dong, Jiahao Chen +5
Optical Character Recognition (OCR) enables automatic text extraction from scanned or digitized text images, but it also makes it easy to pirate valuable or sensitive text from the…