Feature Denoising for Improving Adversarial Robustness

computer vision and pattern recognition, 2019.

Cited by: 165|Bibtex|Views468
EI
Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org

Abstract:

Adversarial attacks to image classification systems present challenges to convolutional networks and opportunities for understanding them. This study suggests that adversarial perturbations on images lead to noise in the features constructed by these networks. Motivated by this observation, we develop new network architectures that incr...More

Code:

Data:

Full Text
Your rating :
0

 

Tags
Comments