Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks
文章目錄 概 主要內容 Mustafa A., Khan S., Hayat M., Goecke R., Shen J., Shao L., Adversarial Defense by Restricting the Hidden Space of Deep Neural Networks, arXiv preprint arXiv:1904.00887, 2019. 代碼 概 類似的, 是l
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相關文章
- 1. [paper]Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks
- 2. [paper]ADVERSARIAL REPROGRAMMING OF NEURAL NETWORKS
- 3. Exploring the teaching of deep learning in neural networks
- 4. On the Number of Linear Regions of Deep Neural Networks
- 5. 關於Distillation as a Defense to Adversarial Perturbations against Deep Neural Networks的理解
- 6. The Unreasonable Effectiveness of Recurrent Neural Networks
- 7. [paper]Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
- 8. Domain-Adversarial Training of Neural Networks
- 9. ICLR2014_Intriguing properties of neural networks
- 10. Xavier——Understanding the difficulty of training deep feedforward neural networks