DeepSafe: A Data-Driven Approach for Assessing Robustness of Neural Networks

ATVA, pp. 3-19, 2018.

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Abstract:

Deep neural networks have achieved impressive results in many complex applications, including classification tasks for image and speech recognition, pattern analysis or perception in self-driving vehicles. However, it has been observed that even highly trained networks are very vulnerable to adversarial perturbations. Adding minimal chang...More

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