Adversarial Attacks and Batch Normalization: A Batch Statistics Perspective-Reference-Cited by-同舟云学术

Adversarial Attacks and Batch Normalization: A Batch Statistics Perspective

Author:

Muhammad Awais¹^ORCID,Shamshad Fahad²^ORCID,Bae Sung-Ho¹^ORCID

Affiliation:

1. Department of Computer Science and Engineering, Kyung-Hee University, Yongin, South Korea

2. Computer Vision Department, Mohamed bin Zayed University of Artificial Intelligence, Abu Dhabi, United Arab Emirates

Funder

Institute of Information and Communications Technology Planning and Evaluation

Korean Government [Ministry of Science and ICT (MSIT)]

IITP Grant

Korean Government

Korean Government (MSIT), Artificial Intelligence Convergence Innovation Human Resources Development

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference77 articles.

1. Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks;croce;Proc ICML,2020

3. Recurrent batch normalization;cooijmans;arXiv 1603 09025,2016

5. On the sensitivity of adversarial robustness to input data distributions;ding;Proc ICLR,2019

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