  This document will review the most prominent proposals using multilayer
convolutional architectures. Importantly, the various components of a typical
convolutional network will be discussed through a review of different
approaches that base their design decisions on biological findings and/or sound
theoretical bases. In addition, the different attempts at understanding
ConvNets via visualizations and empirical studies will be reviewed. The
ultimate goal is to shed light on the role of each layer of processing involved
in a ConvNet architecture, distill what we currently understand about ConvNets
and highlight critical open problems.

Computer Vision and Pattern Recognition