Autoencoder Watchdog Outlier Detection for Classifiers
Machine Learning
2021-08-25 v2
Abstract
Neural networks have often been described as black boxes. A generic neural network trained to differentiate between kittens and puppies will classify a picture of a kumquat as a kitten or a puppy. An autoencoder watch dog screens trained classifier/regression machine input candidates before processing, e.g. to first test whether the neural network input is a puppy or a kitten. Preliminary results are presented using convolutional neural networks and convolutional autoencoder watchdogs using MNIST images.
Cite
@article{arxiv.2010.12754,
title = {Autoencoder Watchdog Outlier Detection for Classifiers},
author = {Justin Bui and Robert J Marks},
journal= {arXiv preprint arXiv:2010.12754},
year = {2021}
}
Comments
7 pages, 12 figures