Improving the transferability of adversarial samples with channel switching
Author:
Funder
Key Research and Development Program of Guangdong Province
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence
Link
https://link.springer.com/content/pdf/10.1007/s10489-023-05160-9.pdf
Reference40 articles.
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2. Wei X, Yuan M (2023) Adversarial pan-sharpening attacks for object detection in remote sensing. Pattern Recogn 139:109466. https://doi.org/10.1016/j.patcog.2023.109466
3. Zhang Y, Tan Y, Lu M et al (2023) Towards interpreting vulnerability of object detection models via adversarial distillation. J Info Sec App 72:103410. https://doi.org/10.1016/j.jisa.2022.103410
4. Ryu G, Park H, Choi D (2021) Adversarial attacks by attaching noise markers on the face against deep face recognition. J Info Sec App 60:102874. https://doi.org/10.1016/j.jisa.2021.102874
5. Wang X, Cai M, Sohel F et al (2021) Adversarial point cloud perturbations against 3D object detection in autonomous driving systems. Neurocomputing 466:27–36. https://doi.org/10.1016/j.neucom.2021.09.027
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