“第十九章 深度学习的问题”版本间的差异
来自cslt Wiki
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==高级读者== | ==高级读者== | ||
| − | * What is adversarial learning [https://bdtechtalks.com/2020/07/15/machine-learning-adversarial-examples/] | + | * What is adversarial machine learning [https://bdtechtalks.com/2020/07/15/machine-learning-adversarial-examples/] |
| − | * | + | * Fong R C, Vedaldi A. Interpretable explanations of black boxes by meaningful perturbation[C]//Proceedings of the IEEE international conference on computer vision. 2017: 3429-3437. [https://openaccess.thecvf.com/content_ICCV_2017/papers/Fong_Interpretable_Explanations_of_ICCV_2017_paper.pdf] |
| + | * Szegedy C, Zaremba W, Sutskever I, et al. Intriguing properties of neural networks[J]. arXiv preprint arXiv:1312.6199, 2013. [https://arxiv.org/pdf/1312.6199.pdf] | ||
| + | * Nguyen A, Yosinski J, Clune J. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2015: 427-436. [https://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Nguyen_Deep_Neural_Networks_2015_CVPR_paper.pdf] | ||
| + | * Eykholt K, Evtimov I, Fernandes E, et al. Robust physical-world attacks on deep learning visual classification[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 1625-1634. [http://openaccess.thecvf.com/content_cvpr_2018/papers/Eykholt_Robust_Physical-World_Attacks_CVPR_2018_paper.pdf] | ||
2022年8月8日 (一) 06:29的版本
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高级读者
- What is adversarial machine learning [1]
- Fong R C, Vedaldi A. Interpretable explanations of black boxes by meaningful perturbation[C]//Proceedings of the IEEE international conference on computer vision. 2017: 3429-3437. [2]
- Szegedy C, Zaremba W, Sutskever I, et al. Intriguing properties of neural networks[J]. arXiv preprint arXiv:1312.6199, 2013. [3]
- Nguyen A, Yosinski J, Clune J. Deep neural networks are easily fooled: High confidence predictions for unrecognizable images[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2015: 427-436. [4]
- Eykholt K, Evtimov I, Fernandes E, et al. Robust physical-world attacks on deep learning visual classification[C]//Proceedings of the IEEE conference on computer vision and pattern recognition. 2018: 1625-1634. [5]
