EITGAN: A Transformation-based Network for recovering adversarial examples

EITGAN: A Transformation-based Network for recovering adversarial examples

Adversarial examples have been shown to easily mislead neural networks, and many strategies have been proposed to defend them. To address the problem that most transformation-based defense strategies will degrade the accuracy of clean images, we proposed an Enhanced Image Transformation Generative A...

Full description

Bibliographic Details
Main Authors: Junjie Zhao, Junfeng Wu, James Msughter Adeke, Guangjie Liu, Yuewei Dai
Format: Article
Language:English
Published: AIMS Press 2023-10-01
Series:Electronic Research Archive
Subjects:
enhanced sample
generative adversarial network
adversarial defense
deep learning
adversarial example
image processing
Online Access:https://www.aimspress.com/article/doi/10.3934/era.2023335?viewType=HTML

Internet

https://www.aimspress.com/article/doi/10.3934/era.2023335?viewType=HTML

Similar Items