Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems-Reference-Cited by-同舟云学术

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Fooling the Eyes of Autonomous Vehicles: Robust Physical Adversarial Examples Against Traffic Sign Recognition Systems

Published:2022 Issue: Volume: Page:
ISSN:
Container-title:Proceedings 2022 Network and Distributed System Security Symposium
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Author:

Jia Wei,Lu Zhaojun,Zhang Haichun,Liu Zhenglin,Wang Jie,Qu Gang

Publisher

Internet Society

Cited by 13 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. Fooling Decision-Based Black-Box Automotive Vision Perception Systems in Physical World;IEEE Transactions on Intelligent Transportation Systems;2024-07

2. Road Decals as Trojans: Disrupting Autonomous Vehicle Navigation with Adversarial Patterns;2024 54th Annual IEEE/IFIP International Conference on Dependable Systems and Networks - Supplemental Volume (DSN-S);2024-06-24

3. An Initial Exploration of Employing Large Multimodal Models in Defending Against Autonomous Vehicles Attacks;2024 IEEE Intelligent Vehicles Symposium (IV);2024-06-02

4. Trusted Perception Method for Traffic Signs That Are Physically Attacked;Transportation Research Record: Journal of the Transportation Research Board;2024-05-16

5. Exploring Explainable Artificial Intelligence Techniques for Interpretable Neural Networks in Traffic Sign Recognition Systems;Electronics;2024-01-10

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