Abstract
Deep neural networks for image processing and representation learning are currently applied with great success in tasks for which there is annotation available. Although some architectures are capable of generalizing for different problems, there is a gap in the study of unsupervised representation learning, or also under the context of few shot learning. In this sense, this project propo…