[論文解讀]Feature-Guided Black-Box Safety Testing of Deep Neural Networks
Feature-Guided Black-Box Safety Testing of Deep Neural Networks 深度神經網絡的功能導向黑盒安全測試 總結: 一種使用蒙特卡洛樹搜索的方式來獲取反例的方法,使用SIFT提取關鍵點,並採用兩個玩家回合制的方式對關鍵點進行操作. 文章目錄 Feature-Guided Black-Box Safety Testing of Deep Neu
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相關文章
- 1. [論文解讀] Concolic Testing for Deep Neural Networks
- 2. 論文閱讀：Deep Neural Networks for Object Detection
- 3. 論文閱讀《Knowledge Projection for Effective Design of Thinner and Faster Deep Neural Networks》
- 4. Knowledge Projection for Effective Design of Thinner and Faster Deep Neural Networks論文初讀
- 5. 【論文快讀】Intriguing properties of neural networks(2014)
- 6. MUNN：Mutation Analysis of neural networks論文閱讀
- 7. [deep compression] compressing deep neural networks 論文學習
- 8. 論文《On the Number of Linear Regions of Deep Neural Networks》翻譯
- 9. 論文解析-《Understanding the difficulty of training deep feedforward neural networks》
- 10. [論文解讀]Towards Improved Testing For Deep Learning