DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks

arXiv: Neural and Evolutionary Computing, Volume abs/1710.00486, 2017.

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Abstract:

Deep neural networks have become widely used, obtaining remarkable results in domains such as computer vision, speech recognition, natural language processing, audio recognition, social network filtering, machine translation, and bio-informatics, where they have produced results comparable to human experts. However, these networks can be ...More

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