Convolutional Neural Networks in Visual Computing: A Concise Guide covers the fundamentals of designing and deploying deep convolutional neural network architectures. It is intended to serve as a beginner’s guide for engineers and students who want to have a quick start on learning and/or building deep vision systems. This book provides a good theoretical and practical understanding along with a complete toolkit for basic information and knowledge required to understand and build convolutional neural networks (CNN) from scratch. The book focuses explicitly on convolutional neural networks, filtering out other material that co-occur in many advanced books on CNN topics.
This book is:
This website is a supplementary to the book and contains code and implementations, color illustrations of some figures and additional discusions. This book also led to a graduate level course that was taught in the Spring of 2017 at Arizona State University, lectures and materials for which is also avialable here.