Studying Invariances of Trained Convolutional Neural Networks

15 March 2018

Papers citing "Studying Invariances of Trained Convolutional Neural Networks"

4 / 4 papers shown

Title
Invariance Measures for Neural Networks F. Quiroga J. Torrents-Barrena Laura Lanzarini Domenec Puig-Valls 32 4 0 26 Oct 2023
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 128 58 0 29 Apr 2021
A Self-Supervised Feature Map Augmentation (FMA) Loss and Combined Augmentations Finetuning to Efficiently Improve the Robustness of CNNs Nikhil Kapoor C. Yuan Jonas Löhdefink Roland S. Zimmermann Serin Varghese Fabian Hüger Nico M. Schmidt Peter Schlicht Tim Fingscheidt AAML 39 4 0 02 Dec 2020
Why do deep convolutional networks generalize so poorly to small image transformations? Aharon Azulay Yair Weiss 108 563 0 30 May 2018