[论文解读]Feature-Guided Black-Box Safety Testing of Deep Neural Networks

时间 2021-01-02

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Feature-Guided Black-Box Safety Testing of Deep Neural Networks 深度神经网络的功能导向黑盒安全测试总结: 一种使用蒙特卡洛树搜索的方式来获取反例的方法,使用SIFT提取关键点,并采用两个玩家回合制的方式对关键点进行操作. 文章目录 Feature-Guided Black-Box Safety Testing of Deep Neu

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1. [论文解读] Concolic Testing for Deep Neural Networks
2. 论文阅读：Deep Neural Networks for Object Detection
3. 论文阅读《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论文初读
5. 【论文快读】Intriguing properties of neural networks(2014)
6. MUNN：Mutation Analysis of neural networks论文阅读
7. [deep compression] compressing deep neural networks 论文学习
8. 论文《On the Number of Linear Regions of Deep Neural Networks》翻译
9. 论文解析-《Understanding the difficulty of training deep feedforward neural networks》
10. [论文解读]Towards Improved Testing For Deep Learning

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