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Hyperspectral Image Analysis

Saurabh Prasad
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      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. 
      Format: Hardback CONTRIBUTORS: Saurabh Prasad EAN: 9783030386160 COUNTRY: Switzerland PAGES: WEIGHT: 869 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2020-04-28 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Software Development & Engineering / Computer Graphics, TECHNOLOGY & ENGINEERING / Electronics / General, TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems WIDTH: 155 cm SPINE:

      Book Themes:

      Geographical information systems, geodata and remote sensing, Imaging systems and technology, Machine learning, Computer vision, Digital signal processing (DSP), Image processing

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      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.
      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. 
      Format: Hardback CONTRIBUTORS: Saurabh Prasad EAN: 9783030386160 COUNTRY: Switzerland PAGES: WEIGHT: 869 g HEIGHT: 235 cm
      PUBLISHED BY: Springer Nature Switzerland AG DATE PUBLISHED: 2020-04-28 CITY: GENRE: COMPUTERS / Artificial Intelligence / General, COMPUTERS / Software Development & Engineering / Computer Graphics, TECHNOLOGY & ENGINEERING / Electronics / General, TECHNOLOGY & ENGINEERING / Remote Sensing & Geographic Information Systems WIDTH: 155 cm SPINE:

      Book Themes:

      Geographical information systems, geodata and remote sensing, Imaging systems and technology, Machine learning, Computer vision, Digital signal processing (DSP), Image processing

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      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.

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