Analyzing ImageNet with Spectral Relevance Analysis: Towards ImageNet un-Hans'ed

22 Dec 2019Christopher J. AndersTalmaj MarinčDavid NeumannWojciech SamekKlaus-Robert MüllerSebastian Lapuschkin

Today's machine learning models for computer vision are typically trained on very large (benchmark) data sets with millions of samples. These may, however, contain biases, artifacts, or errors that have gone unnoticed and are exploited by the model... (read more)

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