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Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era

Language EnglishEnglish
Book Hardback
Book Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era GARCIA-RODRIGUEZ
Libristo code: 37078759
Publishers IGI Global, November 2022
In recent decades, there has been an increasing interest in using machine learning and, in the last... Full description
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In recent decades, there has been an increasing interest in using machine learning and, in the last few years, deep learning methods combined with other vision and image processing techniques to create systems that solve vision problems in different fields. There is a need for academicians, developers, and industry-related researchers to present, share, and explore traditional and new areas of computer vision, machine learning, deep learning, and their combinations to solve problems. The Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era is designed to serve researchers and developers by sharing original, innovative, and state-of-the-art algorithms and architectures for applications in the areas of computer vision, image processing, biometrics, virtual and augmented reality, and more. It integrates the knowledge of the growing international community of researchers working on the application of machine learning and deep learning methods in vision and robotics. Covering topics such as brain tumor detection, heart disease prediction, and medical image detection, this premier reference source is an exceptional resource for medical professionals, faculty and students of higher education, business leaders and managers, librarians, government officials, researchers, and academicians.

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About the book

Full name Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era
Language English
Binding Book - Hardback
Date of issue 2022
Number of pages 400
EAN 9781799888925
ISBN 1799888924
Libristo code 37078759
Publishers IGI Global
Weight 1449
Dimensions 216 x 279 x 30
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