Unsupervised Adversarial Defense through Tandem Deep Image Priors

Unsupervised Adversarial Defense through Tandem Deep Image Priors

Deep neural networks are vulnerable to the adversarial example synthesized by adding imperceptible perturbations to the original image but can fool the classifier to provide wrong prediction outputs. This paper proposes an image restoration approach which provides a strong defense mechanism to provi...

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Bibliographic Details
Main Authors:	Yu Shi, Cien Fan, Lian Zou, Caixia Sun, Yifeng Liu
Format:	Article
Language:	English
Published:	MDPI AG 2020-11-01
Series:	Electronics
Subjects:	adversarial example deep learning image restoration unsupervised learning
Online Access:	https://www.mdpi.com/2079-9292/9/11/1957

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