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[R] MNIST-C: A Robustness Benchmark for Computer Vision

We apply simple corruptions to MNIST to create a new dataset for the purpose of measuring non-adversarial robustness in computer vision models. We then evaluate various models on MNIST-C and find that a simple CNN outperforms various adversarial defenses and alternative architectures by a wide margin.

Paper: https://arxiv.org/abs/1906.02337

Code: https://github.com/google-research/mnist-c

submitted by /u/normanmu
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.