A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined
Augmentations Finetuning to Efficiently Improve the Robustness of CNNs

A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs

2 December 2020

Jonas Löhdefink

Roland S. Zimmermann

Nico M. Schmidt

Tim Fingscheidt

Papers citing "A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs"

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