Convolutional Neural Networks in Visual Computing
by Baoxin Li, Ragav Venkatesan
This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems.
Paperback
English
Brand New
Publisher Description
This book covers the fundamentals in designing and deploying techniques using deep architectures. It is intended to serve as a beginner's guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good theoretical and practical understanding and a complete toolkit of 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 deep learning books on CNN topics.
Table of Contents
Dedication; Acknowledgements; About the Author; Preface ; Chapter 1: Introduction to visual computing; Chapter 2: Learning as a regression problem; Chapter 3: Artificial neural networks; Chapter 4: Convolutional neural networks; Chapter 5: Modern and novel usages of CNNs; Appendix; Postscript
Details
