Web: http://arxiv.org/abs/2108.09375

June 16, 2022, 1:11 a.m. | Glauco Amigo, Justin M. Bui, Charles Baylis, Robert J. Marks

cs.LG updates on arXiv.org arxiv.org

The identification of out-of-distribution content is critical to the
successful implementation of neural networks. Watchdog techniques have been
developed to support the detection of these inputs, but the performance can be
limited by the amount of available data. Generative adversarial networks have
displayed numerous capabilities, including the ability to generate facsimiles
with excellent accuracy. This paper presents and empirically evaluates a
multi-tiered watchdog, which is developed using GAN generated data, for
improved out-of-distribution detection. The cascade watchdog uses adversarial
training …

arxiv detection lg

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

Machine Learning Researcher - Saalfeld Lab

@ Howard Hughes Medical Institute - Chevy Chase, MD | Ashburn, Virginia

Project Director, Machine Learning in US Health

@ ideas42.org | Remote, US

Data Science Intern

@ NannyML | Remote

Machine Learning Engineer NLP/Speech

@ Play.ht | Remote

Research Scientist, 3D Reconstruction

@ Yembo | Remote, US

Clinical Assistant or Associate Professor of Management Science and Systems

@ University at Buffalo | Buffalo, NY