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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Majestic Books, Hounslow, Regno Unito
EUR 66,98
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 63,37
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 63,36
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 63,95
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
EUR 73,04
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 77,27
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Da: GreatBookPrices, Columbia, MD, U.S.A.
Condizione: New.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2023
ISBN 10: 1032428325 ISBN 13: 9781032428321
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: new. Hardcover. This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the individual sample as mean training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields.Key features:Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classesDiscusses range of fuzzy/deep learning models capable to extract specific single class and separates noiseDescribes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a classSupports multi-sensor and multi-temporal data processing through in-house SMIC softwareIncludes case studies and practical applications for single class mappingThis book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas. This book brings consolidated information in the form of fuzzy machine and deep learning models for single class mapping from multi-sensor multi-temporal remote sensing images at one place. It provides information about capabilities of multi-spectral and hyperspectral images, fuzzy machine learning models supported by case studies. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Revaluation Books, Exeter, Regno Unito
EUR 92,33
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Aggiungi al carrelloPaperback. Condizione: Brand New. 178 pages. 9.18x6.12x9.21 inches. In Stock.
EUR 54,66
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Da: Majestic Books, Hounslow, Regno Unito
EUR 119,45
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 113,64
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 113,95
Quantità: 8 disponibili
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 113,62
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Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. 1st edition NO-PA16APR2015-KAP.
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2023
ISBN 10: 1032428325 ISBN 13: 9781032428321
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 105,19
Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book elaborates fuzzy machine and deep learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the individual sample as mean training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields.Key features:Focuses on use of multi-sensor, multi-temporal data while handling spectral overlap between classesDiscusses range of fuzzy/deep learning models capable to extract specific single class and separates noiseDescribes pre-processing while using spectral, textural, CBSI indices, and back scatter coefficient/Radar Vegetation Index (RVI) Discusses the role of training data to handle the heterogeneity within a classSupports multi-sensor and multi-temporal data processing through in-house SMIC softwareIncludes case studies and practical applications for single class mappingThis book is intended for graduate/postgraduate students, research scholars, and professionals working in environmental, geography, computer sciences, remote sensing, geoinformatics, forestry, agriculture, post-disaster, urban transition studies, and other related areas. This book brings consolidated information in the form of fuzzy machine and deep learning models for single class mapping from multi-sensor multi-temporal remote sensing images at one place. It provides information about capabilities of multi-spectral and hyperspectral images, fuzzy machine learning models supported by case studies. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
EUR 129,43
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Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 133,59
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EUR 97,19
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Da: Revaluation Books, Exeter, Regno Unito
EUR 168,76
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Aggiungi al carrelloHardcover. Condizione: Brand New. 184 pages. 9.19x6.13x0.59 inches. In Stock.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 76,89
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Aggiungi al carrelloPAP. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 73,98
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Aggiungi al carrelloPAP. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: Revaluation Books, Exeter, Regno Unito
EUR 68,16
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 178 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand.
Da: PBShop.store US, Wood Dale, IL, U.S.A.
EUR 135,98
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Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 131,53
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Aggiungi al carrelloHRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 92,70
Quantità: 1 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book brings consolidated information in the form of fuzzy machine and deep learning models for single class mapping from multi-sensor multi-temporal remote sensing images at one place. It provides information about capabilities of multi-spectral and hyperspectral images, fuzzy machine learning models supported by case studies.