Web: http://arxiv.org/abs/2205.05167

May 12, 2022, 1:11 a.m. | Dakarai Crowder, Girik Malik

cs.LG updates on arXiv.org arxiv.org

Recent neural network architectures have claimed to explain data from the
human visual cortex. Their demonstrated performance is however still limited by
the dependence on exploiting low-level features for solving visual tasks. This
strategy limits their performance in case of out-of-distribution/adversarial
data. Humans, meanwhile learn abstract concepts and are mostly unaffected by
even extreme image distortions. Humans and networks employ strikingly different
strategies to solve visual tasks. To probe this, we introduce a novel set of
image transforms and evaluate …

arxiv cv humans image machines on robustness

More from arxiv.org / cs.LG updates on arXiv.org

Director, Applied Mathematics & Computational Research Division

@ Lawrence Berkeley National Lab | Berkeley, Ca

Business Data Analyst

@ MainStreet Family Care | Birmingham, AL

Assistant/Associate Professor of the Practice in Business Analytics

@ Georgetown University McDonough School of Business | Washington DC

Senior Data Science Writer

@ NannyML | Remote

Director of AI/ML Engineering

@ Armis Industries | Remote (US only), St. Louis, California

Digital Analytics Manager

@ Patagonia | Ventura, California