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This book introduces hyperspectral remote sensing as a transformative imaging technology, capturing intricate details across multiple spectral bands. Originating from a doctoral thesis, the book bridges academic exploration and practical applications in hyperspectral image classification. It pioneers novel methodologies using deep learning and machine learning, featuring the Deep Adversarial Learning Framework for enhanced accuracy. The text explores groundbreaking approaches employing principal component analysis, empirical mode decomposition, and Support Vector Machines. A semi-supervised classification method inspired by Cycle-GANs is also presented. The book aims to offer a comprehensive understanding of hyperspectral imaging, its methodologies, and practical implications, serving as a valuable resource for students, researchers, and practitioners in the field.
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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ISBN 10: 6207459091
ISBN 13: 9786207459094
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207459091
ISBN 13: 9786207459094
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book introduces hyperspectral remote sensing as a transformative imaging technology, capturing intricate details across multiple spectral bands. Originating from a doctoral thesis, the book bridges academic exploration and practical applications in hyp. Seller Inventory # 1385924817
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book introduces hyperspectral remote sensing as a transformative imaging technology, capturing intricate details across multiple spectral bands. Originating from a doctoral thesis, the book bridges academic exploration and practical applications in hyperspectral image classification. It pioneers novel methodologies using deep learning and machine learning, featuring the Deep Adversarial Learning Framework for enhanced accuracy. The text explores groundbreaking approaches employing principal component analysis, empirical mode decomposition, and Support Vector Machines. A semi-supervised classification method inspired by Cycle-GANs is also presented. The book aims to offer a comprehensive understanding of hyperspectral imaging, its methodologies, and practical implications, serving as a valuable resource for students, researchers, and practitioners in the field.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 112 pp. Englisch. Seller Inventory # 9786207459094
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features | An In-Depth Guide to Advanced Techniques and Best Practices in Hyperspectral Image Analysis for Unleashing Insights
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ISBN 13: 9786207459094
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Taschenbuch. Condition: Neu. Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features | An In-Depth Guide to Advanced Techniques and Best Practices in Hyperspectral Image Analysis for Unleashing Insights | Subba Reddy Tatireddy (u. a.) | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207459094 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Seller Inventory # 128478372
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features : An In-Depth Guide to Advanced Techniques and Best Practices in Hyperspectral Image Analysis for Unleashing Insights
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LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207459091
ISBN 13: 9786207459094
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book introduces hyperspectral remote sensing as a transformative imaging technology, capturing intricate details across multiple spectral bands. Originating from a doctoral thesis, the book bridges academic exploration and practical applications in hyperspectral image classification. It pioneers novel methodologies using deep learning and machine learning, featuring the Deep Adversarial Learning Framework for enhanced accuracy. The text explores groundbreaking approaches employing principal component analysis, empirical mode decomposition, and Support Vector Machines. A semi-supervised classification method inspired by Cycle-GANs is also presented. The book aims to offer a comprehensive understanding of hyperspectral imaging, its methodologies, and practical implications, serving as a valuable resource for students, researchers, and practitioners in the field. Seller Inventory # 9786207459094
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Mastering Hyperspectral Imaging using ML and Spatial-Spectral Features
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ISBN 13: 9786207459094
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