Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images With Different Patch Sizes and Perturbation Ratios-Reference-Cited by-同舟云学术

Robust Adversarial Attack Against Explainable Deep Classification Models Based on Adversarial Images With Different Patch Sizes and Perturbation Ratios

Published:2021 Issue: Volume:9 Page:133049-133061
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Le Thi-Thu-Huong^ORCID,Kang Hyoeun^ORCID,Kim Howon^ORCID

Funder

Institute of Information and Communications Technology Planning and Evaluation (IITP) Grant through the Korean Government [Ministry of Science and ICT (MSIT)]

Technology Innovation Program (Developed Onestop Smart Factory Integrated Package For Machine Robot Industry) through the Ministry of Trade, Industry and Energy (MOTIE), South Korea

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09548896.pdf?arnumber=9548896

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