Universal Adversarial Perturbation of SAR Images for Deep Learning Based Target Classification-Reference-Cited by-同舟云学术

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Universal Adversarial Perturbation of SAR Images for Deep Learning Based Target Classification

Published:2021-05-07 Issue: Volume: Page:
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Container-title:2021 IEEE 4th International Conference on Electronics Technology (ICET)
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Author:

Wang Lulu,Wang Xiaolei,Ma Shixin,Zhang Yi

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9450847/9450892/09450944.pdf?arnumber=9450944

Cited by 8 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. An adversarial example attack method based on predicted bounding box adaptive deformation in optical remote sensing images;PeerJ Computer Science;2024-05-28

2. Black-Box Universal Adversarial Attack for DNN-Based Models of SAR Automatic Target Recognition;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. Adversarial Robust Scene Classification based on Proactive-Reactive Deep Ensemble Defenses;2023 IEEE 6th International Conference on Pattern Recognition and Artificial Intelligence (PRAI);2023-08-18

4. Synthetic Loss Function on SAR Target Detection Based on Deep Learning;2023 6th International Conference on Electronics Technology (ICET);2023-05-12

5. ULAN: A Universal Local Adversarial Network for SAR Target Recognition Based on Layer-Wise Relevance Propagation;Remote Sensing;2022-12-21

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