Benchmarking Neural Network Robustness to Common Corruptions and Perturbations

ICLR 2019 Dan HendrycksThomas 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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