  An autoencoder is a specific type of a neural network, which is mainly
designed to encode the input into a compressed and meaningful representation,
and then decode it back such that the reconstructed input is similar as
possible to the original one. This chapter surveys the different types of
autoencoders that are mainly used today. It also describes various applications
and use-cases of autoencoders.

Machine Learning;Computer Vision and Pattern Recognition;Machine Learning