Convolutional Neural Networks in Visual Computing: A Concise Guide

— —

Ragav Venkatesan (Arizona State University, Tempe, USA) Baoxin Li (Arizona State University, Tempe, USA)

Convolutional Neural Networks in Visual Computing

A Concise Guide

Ragav Venkatesan (Arizona State University, Tempe, USA), Baoxin Li (Arizona State University, Tempe, USA)

$152

Paperback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

CRC Press
07 September 2017

Automatic control engineering; Neural networks & fuzzy systems

Series: Data-Enabled Engineering

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.

By: Ragav Venkatesan (Arizona State University Tempe USA), Baoxin Li (Arizona State University, Tempe, USA)
Imprint: CRC Press
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 272g
ISBN: 9781138747951
ISBN 10: 1138747955
Series: Data-Enabled Engineering
Pages: 168
Publication Date: 07 September 2017
Audience: College/higher education , College/higher education , A / AS level , Further / Higher Education
Format: Paperback
Publisher's Status: Active

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

Ragav Venkatesan is currently completing his Ph.D. study in Computer Science in the School of Computing, Informatics and Decision Systems Engineering at Arizona State University. He has been a Research Associate with the Visual Representation and Processing Group in ASU, and has worked as a Teaching Assistant for several graduate-level courses in machine learning, pattern recognition, video processing and computer vision. Prior to this, he was a Research Assistant with the Image Processing and Applications Lab in the School of Electrical & Computer Engineering at ASU, where he obtained an M.S. degree in 2012. From 2013 to 2014, Venkatesan was with the Intel Corporation as a computer vision research intern working on technologies for autonomous vehicles. Venkatesan regularly serves as a reviewer for several peer-reviewed journals and conferences in machine learning and computer vision. Baoxin Li received his Ph.D. in electrical engineering from the University of Maryland, College Park, in 2000. He is currently a Professor and Chair of the Computer Science and Engineering program, and a Graduate Faculty in Electrical Engineering and Computer Engineering programs at Arizona State University, Tempe. From 2000 to 2004, he was a Senior Researcher with SHARP Laboratories of America, Camas, Washington, where he was a technical lead in developing SHARP’s trademarked HiMPACT Sports technologies. From 2003–2004, he was also an Adjunct Professor with the Portland State University, Oregon. He holds eighteen issued U.S. patents and his current research interests include computer vision and pattern recognition, multimedia, social computing, machine learning, and assistive technologies. He won twice the SHARP Laboratories’ President Award, in 2001 and 2004 respectively. He also won the SHARP Laboratories’ Inventor of the Year Award in 2002. He was a recipient of the National Science Foundation’s CAREER Award.