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E. R. Davies (editor) - Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition)

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Advanced Methods and Deep Learning in Computer Vision (Computer Vision and Pattern Recognition): summary, description and annotation

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Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 510 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection.

This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students.

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Advanced Methods and Deep Learning in Computer Vision First edition ER Davies - photo 1
Advanced Methods and Deep Learning in Computer Vision

First edition

E.R. Davies

Matthew A. Turk

Table of Contents List of tables Tables in Chapter 1 Tables in Chapter 2 - photo 2

Table of Contents
List of tables
  1. Tables in Chapter 1
  2. Tables in Chapter 2
  3. Tables in Chapter 3
  4. Tables in Chapter 4
  5. Tables in Chapter 5
  6. Tables in Chapter 7
  7. Tables in Chapter 12
  8. Tables in Chapter 13
  9. Tables in Chapter 14
  10. Tables in Chapter 15
List of figures
  1. Figures in Chapter 1
  2. Figures in Chapter 2
  3. Figures in Chapter 3
  4. Figures in Chapter 4
  5. Figures in Chapter 5
  6. Figures in Chapter 6
  7. Figures in Chapter 7
  8. Figures in Chapter 8
  9. Figures in Chapter 9
  10. Figures in Chapter 10
  11. Figures in Chapter 11
  12. Figures in Chapter 12
  13. Figures in Chapter 13
  14. Figures in Chapter 14
  15. Figures in Chapter 15
Landmarks
Copyright

Academic Press is an imprint of Elsevier

125 London Wall, London EC2Y 5AS, United Kingdom

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Copyright 2022 Elsevier Inc. All rights reserved.

No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher's permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions.

This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.

Library of Congress Cataloging-in-Publication Data

A catalog record for this book is available from the Library of Congress

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-0-12-822109-9

For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher: Mara Conner

Acquisitions Editor: Tim Pitts

Editorial Project Manager: Isabella C. Silva

Production Project Manager: Sojan P. Pazhayattil

Designer: Greg Harris

Typeset by VTeX

Dedication This book is dedicated to my family To cherished memories of my - photo 3

Dedication

This book is dedicated to my family.

To cherished memories of my parents, Arthur and Mary Davies.

To my wife, Joan, for love, patience, support and inspiration.

To my children, Elizabeth, Sarah and Marion, and grandchildren, Jasper, Jerome, Eva, Tara and Pia, for bringing endless joy into my life!

Roy Davies

This book is dedicated to the students, colleagues, friends, and family who have motivated, guided, and supported me in ways too numerous to mention.

To my wife, Kelly, and my children, Hannah and Matt special thanks and appreciation for your love and inspiration.

Matthew Turk

List of contributors

Sathyanarayanan Aakur Computer Science, Oklahoma State University, Stillwater, OK, United States

Yogesh Balaji Department of Computer Science and UMACS, University of Maryland, College Park, MD, United States

Han Cai Massachusetts Institute of Technology, Cambridge, MA, United States

Zhaowei Cai Amazon Web Services, Pasadena, CA, United States

Andrea Cavallaro Centre for Intelligent Sensing, Queen Mary University of London, London, United Kingdom

Rama Chellappa Departments of Electrical and Computer Engineering and Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States

Dongdong Chen Microsoft Cloud & AI, Redmond, WA, United States

E.R. Davies Royal Holloway, University of London, Egham, Surrey, United Kingdom

Michael Felsberg

Computer Vision Laboratory, Department of Electrical Engineering, Linkping University, Linkping, Sweden

School of Engineering, University of KwaZulu-Natal, Durban, South Africa

Cornelia Fermller University of Maryland, Institute for Advanced Computer Studies, Iribe Center for Computer Science and Engineering, College Park, MD, United States

Efstratios Gavves Informatics Institute, University of Amsterdam, Amsterdam, Netherlands

Deepak Gupta Informatics Institute, University of Amsterdam, Amsterdam, Netherlands

Song Han Massachusetts Institute of Technology, Cambridge, MA, United States

Gang Hua Wormpex AI Research, Bellevue, WA, United States

Ali Krayani DITEN, University of Genoa, Genoa, Italy

Ji Lin Massachusetts Institute of Technology, Cambridge, MA, United States

Lucio Marcenaro DITEN, University of Genoa, Genoa, Italy

Michael Maynord University of Maryland, Computer Science Department, Iribe Center for Computer Science and Engineering, College Park, MD, United States

Umberto Michieli Department of Information Engineering, University of Padova, Padova, Italy

Ramy Mounir Computer Science and Engineering, University of South Florida, Tampa, FL, United States

Hien Nguyen Department of Electrical and Computer Engineering, University of Houston, Houston, TX, United States

Changjae Oh Centre for Intelligent Sensing, Queen Mary University of London, London, United Kingdom

Sujoy Paul Google Research, Bangalore, India

Carlo Regazzoni DITEN, University of Genoa, Genoa, Italy

Amit K. Roy-Chowdhury University of California, Riverside, Electrical and Computer Engineering, Riverside, CA, United States

Sudeep Sarkar Computer Science and Engineering, University of South Florida, Tampa, FL, United States

Giulia Slavic DITEN, University of Genoa, Genoa, Italy

Radu Timofte Computer Vision Lab, ETH Zrich, Zrich, Switzerland

Marco Toldo Department of Information Engineering, University of Padova, Padova, Italy

Hassan Ugail Centre for Visual Computing, University of Bradford, Bradford, United Kingdom

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