Learn Computer Vision Using OpenCV With Deep Learning CNNs and RNNs
Build practical applications of computer vision using the OpenCV library with Python. This book discusses different facets of computer vision such as image and object detection, tracking and motion analysis and their applications with examples. The
- PDF / 6,537,800 Bytes
- 163 Pages / 439.42 x 666.14 pts Page_size
- 150 Downloads / 1,085 Views
Learn Computer Vision Using OpenCV With Deep Learning CNNs and RNNs
Sunila Gollapudi Foreword by V Laxmikanth
Learn Computer Vision Using OpenCV: With Deep Learning CNNs and RNNs Sunila Gollapudi Hyderabad, Telangana, India ISBN-13 (pbk): 978-1-4842-4260-5 https://doi.org/10.1007/978-1-4842-4261-2
ISBN-13 (electronic): 978-1-4842-4261-2
Copyright © 2019 by Sunila Gollapudi This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. Trademarked names, logos, and images may appear in this book. Rather than use a trademark symbol with every occurrence of a trademarked name, logo, or image we use the names, logos, and images only in an editorial fashion and to the benefit of the trademark owner, with no intention of infringement of the trademark. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. While the advice and information in this book are believed to be true and accurate at the date of publication, neither the authors nor the editors nor the publisher can accept any legal responsibility for any errors or omissions that may be made. The publisher makes no warranty, express or implied, with respect to the material contained herein. Managing Director, Apress Media LLC: Welmoed Spahr Acquisitions Editor: Celestin Suresh John Development Editor: Matthew Moodie Coordinating Editor: Shrikant Vishwakarma Cover designed by eStudioCalamar Cover image designed by Freepik (www.freepik.com) Distributed to the book trade worldwide by Springer Science+Business Media New York, 233 Spring Street, 6th Floor, New York, NY 10013. Phone 1-800-SPRINGER, fax (201) 348-4505, e-mail [email protected], or visit www.springeronline.com. Apress Media, LLC is a California LLC and the sole member (owner) is Springer Science + Business Media Finance Inc (SSBM Finance Inc). SSBM Finance Inc is a Delaware corporation. For information on translations, please e-mail [email protected], or visit www.apress.com/ rights-permissions. Apress titles may be purchased in bulk for academic, corporate, or promotional use. eBook versions and licenses are also available for most titles. For more information, reference our Print and eBook Bulk Sales web page at www.apress.com/bulk-sales. Any source code or other supplementary material referenced by the author in this book is available to readers on GitHub via the book’s product page, located at www.apress.com/978-1-4842-4260-5. For more detailed information, please visit www.apress.com/source-code. Printed on acid-free
Data Loading...