  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.
