What this book covers

Chapter 1, Introduction to Computer Vision and Training Neural Networks, introduces the reader to the concepts of deep neural networks and their learning process. We shall also learn how to train a neural network model in the most efficient manner. 

Chapter 2, Convolution Neural Network Architectures, explains how a convolutional network is a fundamental part of computer vision and describes how to build a handwritten digit recognizer.

Chapter 3, Transfer Learning and Deep CNN Architectures, delves into the details of widely used deep convolution architectures and how to use transfer learning to get the most out of these architectures. This chapter concludes with the building of a Java application for animal image classification

Chapter 4, Real-Time Object Detection, covers how to additionally mark objects with boundary boxes in real time. We will use these techniques and ideas to build a Java real-time car pedestrian and traffic light detection system that is the basis for autonomous driving.

Chapter 5, Creating Art with Neural Style Transfer, explains how we want to know what deep neural network layers are trying to learn. We will use this intuition and knowledge to build a new lifestyle transfer application in Java that is able to create art.

Chapter 6, Face Recognition, helps the reader to solve the problem of face recognition and ultimately compile a Java face recognition application.