Defending Adversarial Attacks by Correcting logits

26 Jun 2019Yifeng LiLingxi XieYa ZhangRui ZhangYanfeng WangQi Tian

Generating and eliminating adversarial examples has been an intriguing topic in the field of deep learning. While previous research verified that adversarial attacks are often fragile and can be defended via image-level processing, it remains unclear how high-level features are perturbed by such attacks... (read more)

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