Abstract
Deep neural networks are able to not only optimally predict the output but also to transform raw input data into more suitable representations. Such flexibility is accompanied with a large number of parameters that hinder the understanding of network functioning. To help understanding, visualization techniques are employed to gain insight or reinforce evidences that a network is working p…