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Weizhen Xu, Chenyi Zhang, Fangzhen Zhao and Liangda Fang
Adversarial attacks hamper the functionality and accuracy of deep neural networks (DNNs) by meddling with subtle perturbations to their inputs. In this work, we propose a new mask-based adversarial defense scheme (MAD) for DNNs to mitigate the negative e...
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