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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

R2 v1 2026-06-23T19:36:37.237Z