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  • 1
    UID:
    b3kat_BV044660937
    Format: 1 Online-Ressource (VI, 178 p. 71 illus., 61 illus. in color)
    ISBN: 9789811064043
    Series Statement: Cognitive Science and Technology
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-981-10-6402-9
    Language: English
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    UID:
    b3kat_BV045222320
    Edition: 2nd ed
    ISBN: 9781786466563
    Note: Description based on publisher supplied metadata and other sources
    Additional Edition: Erscheint auch als Druck-Ausgabe Baggio, Daniel Lelis Mastering OpenCV 3 - Second Edition Birmingham : Packt Publishing,c2017
    Additional Edition: Erscheint auch als Online-Ausgabe ISBN 978-1-78646-656-3
    Language: English
    Subjects: Computer Science
    RVK:
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    UID:
    b3kat_BV044614191
    Format: 1 online resource (244 pages)
    Edition: 2nd ed
    ISBN: 9781786466563
    Note: Description based on publisher supplied metadata and other sources
    Additional Edition: Erscheint auch als Druck-Ausgabe Baggio, Daniel Lelis Mastering OpenCV 3 - Second Edition Birmingham : Packt Publishing,c2017
    Language: English
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  • 4
    UID:
    b3kat_BV045567763
    Format: iv, 266 Seiten , Illustrationen
    Edition: Third edition
    ISBN: 9781789533576
    Language: English
    Subjects: Computer Science
    RVK:
    Keywords: OpenCV ; Maschinelles Lernen
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  • 5
    UID:
    b3kat_BV047069552
    Format: 1 Online-Ressource (538 Seiten)
    Edition: 1
    ISBN: 9781838641269
    Content: bDelve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms/b h4Key Features/h4 ul liDiscover best practices for engineering and maintaining OpenCV projects /li liExplore important deep learning tools for image classification /li liUnderstand basic image matrix formats and filters/li /ul h4Book Description/h4 OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos.
    Content: In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: ul liMastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millan Escriva/li liLearn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G.
    Content: Mendonca, and Prateek Joshi/li /ul h4What you will learn/h4 ul liStay up-to-date with algorithmic design approaches for complex computer vision tasks /li liWork with OpenCV's most up-to-date API through various projects /li liUnderstand 3D scene reconstruction and Structure from Motion (SfM) /li liStudy camera calibration and overlay augmented reality (AR) using the ArUco module /li liCreate CMake scripts to compile your C++ application /li liExplore segmentation and feature extraction techniques /li liRemove backgrounds from static scenes to identify moving objects for surveillance /li liWork with new OpenCV functions to detect and recognize text with Tesseract/li/ul h4Who this book is for/h4 If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you.
    Language: English
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  • 6
    UID:
    almahu_BV045415306
    Format: 1 Online-Ressource (iv, 259 Seiten) : , Illustrationen, Diagramme (überwiegend farbig).
    Edition: Third edition
    ISBN: 978-1-7895-3926-4
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-1-78953-357-6
    Language: English
    Subjects: Computer Science
    RVK:
    RVK:
    Keywords: OpenCV ; Maschinelles Lernen ; Electronic books
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  • 7
    UID:
    almafu_9959797950902883
    Format: 1 online resource (280 pages)
    Edition: Third edition.
    Content: Work on practical computer vision projects covering advanced object detector techniques and modern deep learning and machine learning algorithms Key Features Learn about the new features that help unlock the full potential of OpenCV 4 Build face detection applications with a cascade classifier using face landmarks Create an optical character recognition (OCR) model using deep learning and convolutional neural networks Book Description Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You'll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You'll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You'll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4. What you will learn Build real-world computer vision problems with working OpenCV code samples Uncover best practices in engineering and maintaining OpenCV projects Explore algorithmic design approaches for complex computer vision tasks Work with OpenCV's most updated API (v4.0.0) through projects Understand 3D scene reconstruction and Structure from Motion (SfM) Study camera calibration and overlay AR using the ArUco Module Who this book is for This book is for those who have a basic knowledge of OpenCV and are competent C++ programmers. You need to have an understanding of some of the more theoretical/mathematical concepts, as we move quite quickly throughout the book.
    Additional Edition: ISBN 1-78953-357-0
    Language: English
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  • 8
    UID:
    almafu_9959870367302883
    Format: 1 online resource (527 pages)
    Edition: 1st edition
    ISBN: 1-83864-126-2
    Series Statement: Learning path
    Content: Delve into practical computer vision and image processing projects and get up to speed with advanced object detection techniques and machine learning algorithms Key Features Discover best practices for engineering and maintaining OpenCV projects Explore important deep learning tools for image classification Understand basic image matrix formats and filters Book Description OpenCV is one of the best open source libraries available and can help you focus on constructing complete projects on image processing, motion detection, and image segmentation. This Learning Path is your guide to understanding OpenCV concepts and algorithms through real-world examples and activities. Through various projects, you'll also discover how to use complex computer vision and machine learning algorithms and face detection to extract the maximum amount of information from images and videos. In later chapters, you'll learn to enhance your videos and images with optical flow analysis and background subtraction. Sections in the Learning Path will help you get to grips with text segmentation and recognition, in addition to guiding you through the basics of the new and improved deep learning modules. By the end of this Learning Path, you will have mastered commonly used computer vision techniques to build OpenCV projects from scratch. This Learning Path includes content from the following Packt books: Mastering OpenCV 4 - Third Edition by Roy Shilkrot and David Millan Escriva Learn OpenCV 4 By Building Projects - Second Edition by David Millan Escriva, Vinicius G. Mendonca, and Prateek Joshi What you will learn Stay up-to-date with algorithmic design approaches for complex computer vision tasks Work with OpenCV's most up-to-date API through various projects Understand 3D scene reconstruction and Structure from Motion (SfM) Study camera calibration and overlay augmented reality (AR) using the ArUco module Create CMake scripts to compile your C++ application Explore segmentation and feature extraction techniques Remove backgrounds from static scenes to identify moving objects for surveillance Work with new OpenCV functions to detect and recognize text with Tesseract Who this book is for If you are a software developer with a basic understanding of computer vision and image processing and want to develop interesting computer vision applications with OpenCV, this Learning Path is for you. Prior knowledge of C++ and familiarity with mathematical concepts will help you better ...
    Additional Edition: ISBN 1-83864-467-9
    Language: English
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