Advances in Adversarial Attacks and Defenses in Computer Vision: A Survey-Reference-Cited by-同舟云学术

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Advances in Adversarial Attacks and Defenses in Computer Vision: A Survey

Published:2021 Issue: Volume:9 Page:155161-155196
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Akhtar Naveed^ORCID,Mian Ajmal^ORCID,Kardan Navid,Shah Mubarak^ORCID

Funder

Defense Advanced Research Projects Agency

Australian Research Council Discovery

Office of National Intelligence National Intelligence Postdoctoral Grant

Australian Government

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/6287639/9312710/09614158.pdf?arnumber=9614158

Cited by 144 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Sample selection of adversarial attacks against traffic signs;Neural Networks;2024-12

2. A review of black-box adversarial attacks on image classification;Neurocomputing;2024-12

3. Exploring the Security Landscape of Underwater Positioning and Navigation Systems: An Attack Surface Analysis;2024 IEEE 49th Conference on Local Computer Networks (LCN);2024-10-08

4. State-of-the-art optical-based physical adversarial attacks for deep learning computer vision systems;Expert Systems with Applications;2024-09

5. Transferable adversarial attack based on sensitive perturbation analysis in frequency domain;Information Sciences;2024-09

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