Acknowledgement
본 연구는 국방암호기술 특화연구센터(UD210027XD)를 통한 방위사업청과 국방과학연구소의 연구비 지원으로 수행되었습니다
References
- Anagnostopoulos, Georgios C. "SVM-based target recognition from synthetic aperture radar images using target region outline descriptors." {Nonlinear Analysis: Theory, Methods \& Applications} 71.12 (2009): e2934-e2939. https://doi.org/10.1016/j.na.2009.07.030
- Kechagias-Stamatis, Odysseas, and Nabil Aouf. "Automatic target recognition on synthetic aperture radar imagery: A survey." IEEE Aerospace and Electronic Systems Magazine 36.3 (2021): 56-81. https://doi.org/10.1109/MAES.2021.3049857
- Li, Haifeng, et al. "Adversarial examples for CNN-based SAR image classification: An experience study." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 14 (2020): 1333-1347. https://doi.org/10.1109/JSTARS.2020.3038683
- Peng, Bowen, et al. "Scattering model guided adversarial examples for SAR target recognition: Attack and defense." IEEE Transactions on Geoscience and Remote Sensing 60 (2022): 1-17 https://doi.org/10.1109/TGRS.2022.3213305
- Qin, Weibo, Bo Long, and Feng Wang. "SCMA: A Scattering Center Model Attack on CNN-SAR Target Recognition." {IEEE Geoscience and Remote Sensing Letters 20 (2023): 1-5.
- Zhou, Junfan, et al. "Attributed scattering center guided adversarial attack for DCNN SAR target recognition." IEEE Geoscience and Remote Sensing Letters 20 (2023): 1-5.
- Peng, Bowen, et al. "An Empirical Study of Fully Black-Box and Universal Adversarial Attack for SAR Target Recognition." Remote Sensing 14.16 (2022): 4017.
- hakraborty, Anirban, et al. "Adversarial attacks and defences: A survey." arXiv preprint arXiv:1810.00069 (2018).
- Su, Jiawei, Danilo Vasconcellos Vargas, and Kouichi Sakurai. "one pixel attack for fooling deep neural networks." IEEE Transactions on Evolutionary Computation 23.5 (2019): 828-841. https://doi.org/10.1109/TEVC.2019.2890858
- Xiao, Chaowei, et al. "Generating adversarial examples with adversarial networks." arXiv preprint arXiv:1801.02610 (2018).
- Xie, Cihang, et al. "Improving transferability of adversarial examples with input diversity." Proceedings of the IEEE/CVF conference on computer vision and pattern recognition. 2019.
- Wang, Xiaosen, and Kun He. "Enhancing the transferability of adversarial attacks through variance tuning." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.
- Malmgren-Hansen, David, and Morten Nobel-J. "Convolutional neural networks for SAR image segmentation." 2015 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT). IEEE, 2015.
- C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus, "Intriguing Properties of Neural Networks," in ICLR, 2014.
- Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." arXiv preprint arXiv:1412.6572 (2014).
- Moosavi-Dezfooli, Seyed-Mohsen, Alhussein Fawzi, and Pascal Frossard. "Deepfool: a simple and accurate method to fool deep neural networks." Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.
- A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu, "Towards Deep Learning Models Resistant to Adversarial Attacks," in ICLR, 2018.
- Carlini, Nicholas, and David Wagner. "Towards evaluating the robustness of neural networks." 2017 ieee symposium on security and privacy (sp). Ieee, 2017.