Classification is one of the most important tasks carried out by intelligent systems. Recent
works have proposed deep learning to solve the classification problem. While such …

Representation learning plays a crucial rule in pattern recognition. Recently, sparse
representation (SR) has become a popular technique in high-dimensional signal …

The aim of parametric classification is to predict the target class of a new sample, under the
hypothesis of known fitted distribution. A major drawback of this approach is the uncertainty …

This thesis deals with the problem of localization of dependent elderly people using wireless
sensor networks. Each person is equipped with a bracelet that consists of a sensor capable …

In this chapter, we briefly cover sparse representation classification for single modality and
its extension for multimodal data. Understanding SRC is vital for the discussions in Chapters …