LEA<sup>2</sup>: A Lightweight Ensemble Adversarial Attack via Non-overlapping Vulnerable Frequency Regions-Reference-Cited by-同舟云学术

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LEA²: A Lightweight Ensemble Adversarial Attack via Non-overlapping Vulnerable Frequency Regions

Published:2023-10-01 Issue: Volume: Page:4487-4498
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Qian Yaguan¹,He Shuke¹,Zhao Chenyu¹,Sha Jiaqiang¹,Wang Wei²,Wang Bin³

Affiliation:

1. Zhejiang University of Science and Technology,School of Science,Hangzhou,China

2. Beijing Jiaotong University,Beijing Key Laboratory of Security and Privacy in Intelligent Transportation,China

3. Application and Cybersecurity,Zhejiang Key Laboratory of Multidimensional Perception Technology,China

Funder

National Natural Science Foundation of China

Zhejiang University

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10377345.pdf?arnumber=10377345

Reference45 articles.

1. Towards Evaluating the Robustness of Neural Networks

2. SMGEA: A New Ensemble Adversarial Attack Powered by Long-Term Gradient Memories

3. Amplitude-Phase Recombination: Rethinking Robustness of Convolutional Neural Networks in Frequency Domain

4. ImageNet: A large-scale hierarchical image database

5. Frequency-Tuned Universal Adversarial Attacks on Texture Recognition

Cited by 1 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. How Deep Learning Sees the World: A Survey on Adversarial Attacks & Defenses;IEEE Access;2024

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