Hyperspectral Image Analysis : Advances in Machine Learning and Signal Processing
Language: English
Published by Springer, 2021
Series: Book 76 of 86 - Advances in Computer Vision and Pattern Recognition
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 154.07
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - 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,anomalouschange 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 ofimage 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.…
Seller Inventory # 9783030386191
- Title
- Hyperspectral Image Analysis : Advances in Machine Learning and Signal Processing
- Author
- Jocelyn Chanussot
- Publisher
- Springer
- Publication year
- 2021
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 3030386198
- ISBN 13
- 9783030386191
- Item weight
- 709 grams
- Dimensions
- 235x155x26 mm
- Series
- Book 76 of 86: Advances in Computer Vision and Pattern Recognition
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 ofimage 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.
"Synopsis" may belong to another edition of this title.
About the Author
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.
"About the title" may belong to another edition of this title.
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