第十九章 深度学习的问题

来自cslt Wiki
2022年8月8日 (一) 06:45Cslt讨论 | 贡献的版本

跳转至: 导航搜索


教学资料


扩展阅读

  • 维基百科:可解释人工智能[1][2]
  • 知乎:可解释人工智能[3]
  • 脆弱的神经网络:UC Berkeley详解对抗样本生成机制 [4]


视频展示

演示链接

开发者资源

高级读者

  • What is adversarial machine learning [5]
  • 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. [6]
  • Szegedy C, Zaremba W, Sutskever I, et al. Intriguing properties of neural networks[J]. arXiv preprint arXiv:1312.6199, 2013. [7]
  • 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. [8]
  • 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. [9]
  • 可解释人工智能导论 [10]