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Advances in Computer Vision and Pattern Recognition

Hyperspectral Image Analysis

Advances in Machine Learning and Signal Processing

Editors: Prasad, Saurabh, Chanussot, Jocelyn (Eds.)

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  • Provides a comprehensive review of the state of the art in hyperspectral image analysis
  • Presents perspectives from experts who are pioneers in a broad range of signal processing and machine learning fields related to hyperspectral imaging and remote sensing
  • Is suitable both as a reference book and as a textbook for advanced graduate courses on multi-dimensional image processing
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イーブック ¥13,477
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  • ISBN 978-3-030-38617-7
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この書籍について

This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful. 


著者について

Dr. Saurabh Prasad is an Associate Professor at the Department of Electrical and Computer Engineering at the University of Houston, TX, USA.

Dr. Jocelyn Chanussot is a Professor in the Signal and Images Department at Grenoble Institute of Technology, France.

Table of contents (15 chapters)

Table of contents (15 chapters)
  • Introduction

    Pages 1-4

    Prasad, Saurabh (et al.)

  • Machine Learning Methods for Spatial and Temporal Parameter Estimation

    Pages 5-35

    Moreno-Martínez, Álvaro (et al.)

  • Deep Learning for Hyperspectral Image Analysis, Part I: Theory and Algorithms

    Pages 37-68

    Berisha, Sebastian (et al.)

  • Deep Learning for Hyperspectral Image Analysis, Part II: Applications to Remote Sensing and Biomedicine

    Pages 69-115

    Shahraki, Farideh Foroozandeh (et al.)

  • Advances in Deep Learning for Hyperspectral Image Analysis—Addressing Challenges Arising in Practical Imaging Scenarios

    Pages 117-140

    Zhou, Xiong (et al.)

書籍の購入

イーブック ¥13,477
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-38617-7
  • ウォーターマーク付、 DRMフリー
  • ファイル形式: EPUB, PDF
  • どの電子書籍リーダーからでもすぐにお読みいただけます。
  • ご購入後、すぐにダウンロードしていただけます。
ハードカバー ¥16,847
価格の適用国: Japan (日本円価格は個人のお客様のみ有効) (小計)
  • ISBN 978-3-030-38616-0
  • 個人のお客様には、世界中どこでも配送料無料でお届けします。
  • Immediate ebook access, if available*, with your print order
  • Usually dispatched within 3 to 5 business days.
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書誌情報

Bibliographic Information
Book Title
Hyperspectral Image Analysis
Book Subtitle
Advances in Machine Learning and Signal Processing
Editors
  • Saurabh Prasad
  • Jocelyn Chanussot
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2020
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
イーブック ISBN
978-3-030-38617-7
DOI
10.1007/978-3-030-38617-7
ハードカバー ISBN
978-3-030-38616-0
Series ISSN
2191-6586
Edition Number
1
Number of Pages
VI, 466
Number of Illustrations
26 b/w illustrations, 144 illustrations in colour
Topics

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