Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations

ICLR 2019 Dan HendrycksThomas G. Dietterich

In this paper we establish rigorous benchmarks for image classifier robustness. Our first benchmark, ImageNet-C, standardizes and expands the corruption robustness topic, while showing which classifiers are preferable in safety-critical applications... (read more)

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