Detection of adversarial attacks via disentangling natural images and perturbations
The vulnerability of deep neural networks against adversarial attacks, i.e., imperceptible adversarial perturbations can easily give rise to wrong predictions, poses a huge threat to the security of their real-world deployments. In this paper, a novel Adversarial Detection method via Disentangling N...
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Main Authors: | , , , , |
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格式: | Article |
語言: | English |
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2024
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在線閱讀: | https://hdl.handle.net/10356/178082 |
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