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Published by LAP Lambert Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Published by LAP Lambert Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
Language: English
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Published by LAP Lambert Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Published by LAP Lambert Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Add to basketTaschenbuch. 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: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Published by LAP Lambert Academic Publishing, 2024
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Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Published by LAP LAMBERT Academic Publishing, 2024
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Language: English
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Add to basketPAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Published by LAP LAMBERT Academic Publishing Jan 2024, 2024
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 112 pp. Englisch.
Published by LAP Lambert Academic Publishing, 2024
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Add to basketCondition: 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.
Published by LAP LAMBERT Academic Publishing Jan 2024, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
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Add to basketTaschenbuch. 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.Books on Demand GmbH, Überseering 33, 22297 Hamburg 112 pp. Englisch.
Published by LAP LAMBERT Academic Publishing, 2024
ISBN 10: 6207459091 ISBN 13: 9786207459094
Language: English
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Add to basketTaschenbuch. 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.