Deep Learning: Basics and Convolutional Neural Networks (CNNs)
Maria Vakalopoulou, Stergios Christodoulidis, Ninon Burgos, Olivier Colliot, Vincent Lepetit
Abstract
Abstract Deep learning belongs to the broader family of machine learning methods and currently provides state-of-the-art performance in a variety of fields, including medical applications. Deep learning architectures can be categorized into different groups depending on their components. However, most of them share similar modules and mathematical formulations. In this chapter, the basic concepts of deep learning will be presented to provide a better understanding of these powerful and broadly used algorithms. The analysis is structured around the main components of deep learning architectures, focusing on convolutional neural networks and autoencoders.