132 citations · 285 across the 36 of their papers we have counts for
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cs.LG2021★ 5 cited
Closer Look at the Transferability of Adversarial Examples: How They Fool Different Models Differently
Futa Waseda, Sosuke Nishikawa, Trung-Nghia Le +2
Deep neural networks are vulnerable to adversarial examples (AEs), which have adversarial transferability: AEs generated for the source model can mislead another (target) model's p…
cs.LG2019★ 2 cited
Detecting and Correcting Adversarial Images Using Image Processing Operations
Huy H. Nguyen, Minoru Kuribayashi, Junichi Yamagishi +1
Deep neural networks (DNNs) have achieved excellent performance on several tasks and have been widely applied in both academia and industry. However, DNNs are vulnerable to adversa…