Da: SpringBooks, Berlin, Germania
Prima edizione
EUR 54,99
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Aggiungi al carrelloHardcover. Condizione: Very Good. 1. Auflage. Unread, some shelfwear. Immediately dispatched from Germany.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 127,68
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Da: Books Puddle, New York, NY, U.S.A.
EUR 140,26
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Da: Best Price, Torrance, CA, U.S.A.
EUR 122,13
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Aggiungi al carrelloCondizione: New. SUPER FAST SHIPPING.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 140,91
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Aggiungi al carrelloCondizione: New. In.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 140,90
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Aggiungi al carrelloCondizione: New.
Editore: Springer, Berlin, Springer International Publishing, Springer, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 141,72
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
Editore: Springer, Berlin, Springer International Publishing, Springer, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 143,56
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 151,92
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 154,57
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Books Puddle, New York, NY, U.S.A.
EUR 166,64
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Da: Revaluation Books, Exeter, Regno Unito
EUR 173,64
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Aggiungi al carrelloPaperback. Condizione: Brand New. reprint edition. 131 pages. 9.25x6.10x0.34 inches. In Stock.
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 129,44
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Aggiungi al carrelloCondizione: New.
Editore: Springer-Verlag New York Inc, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Lingua: Inglese
Da: Revaluation Books, Exeter, Regno Unito
EUR 190,26
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Aggiungi al carrelloHardcover. Condizione: Brand New. 131 pages. 9.25x6.25x0.50 inches. In Stock.
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 217,77
Convertire valutaQuantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: New. New. book.
Editore: Springer International Publishing, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 119,56
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces four unique properties related to the nature of spatial data that must be accounted for in any data analysisCovers Spatial AutocorrelationDiscusses Spatial Dependency in Multiple Spatial ScalesEmerging Spatial Big Data.
Editore: Springer International Publishing, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 119,56
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Aggiungi al carrelloGebunden. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduces four unique properties related to the nature of spatial data that must be accounted for in any data analysisCovers Spatial AutocorrelationDiscusses Spatial Dependency in Multiple Spatial ScalesEmerging Spatial Big Data.
Editore: Springer, Berlin, Springer International Publishing, Springer Aug 2018, 2018
ISBN 10: 3319868020 ISBN 13: 9783319868028
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 139,09
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference. 131 pp. Englisch.
Editore: Springer, Berlin, Springer International Publishing, Springer Jul 2017, 2017
ISBN 10: 3319601946 ISBN 13: 9783319601946
Lingua: Inglese
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
EUR 139,09
Convertire valutaQuantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Emerging Spatial Big Data (SBD) has transformative potential in solving many grand societal challenges such as water resource management, food security, disaster response, and transportation. However, significant computational challenges exist in analyzing SBD due to the unique spatial characteristics including spatial autocorrelation, anisotropy, heterogeneity, multiple scales and resolutions which is illustrated in this book.This book also discusses current techniques for, spatial big data science with a particular focus on classification techniques for earth observation imagery big data. Specifically, the authors introduce several recent spatial classification techniques, such as spatial decision trees and spatial ensemble learning. Several potential future research directions are also discussed. This book targets an interdisciplinary audience including computer scientists, practitioners and researchers working in the field of data mining, big data, as well as domain scientists working in earth science (e.g., hydrology, disaster), public safety and public health. Advanced level students in computer science will also find this book useful as a reference. 131 pp. Englisch.
Da: Majestic Books, Hounslow, Regno Unito
EUR 174,39
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 179,42
Convertire valutaQuantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND.