Image Super-Resolution as a Defense Against Adversarial Attacks
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Mustafa, Aamir; Khan, Salman Hameed; Hayat, Munawar; Shen, Jianbing; Shao, Ling
Description
Convolutional Neural Networks have achieved significant success across multiple computer vision tasks. However, they are vulnerable to carefully crafted, human-imperceptible adversarial noise patterns which constrain their deployment in critical security-sensitive systems. This paper proposes a computationally efficient image enhancement approach that provides a strong defense mechanism to effectively mitigate the effect of such adversarial perturbations. We show that deep image restoration...[Show more]
Collections | ANU Research Publications |
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Date published: | 2020 |
Type: | Journal article |
URI: | http://hdl.handle.net/1885/309737 |
Source: | IEEE Transactions on Image Processing |
DOI: | 10.1109/TIP.2019.2940533 |
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Image_Super-Resolution_as_a_Defense_Against_Adversarial_Attacks.pdf | 4.23 MB | Adobe PDF | Request a copy |
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