Thomas G. Dietterich

Benchmarking Neural Network Robustness to Common Corruptions and Surface Variations

2018 · arXiv (Cornell University)

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. Unlike recent robustness research, …