Importo totale (1 articolo articoli):
Destinazione ordine:
kavzoglu taskin (39 risultati)
Vai alla pagina principale dei risultati di ricerca
Filtri di ricerca
Tipo di articolo
- Tutti i tipi di prodotto
- Libri (39)
- Riviste e Giornali (Nessun altro risultato corrispondente a questo perfezionamento)
- Fumetti (Nessun altro risultato corrispondente a questo perfezionamento)
- Spartiti (Nessun altro risultato corrispondente a questo perfezionamento)
- Arte, Stampe e Poster (Nessun altro risultato corrispondente a questo perfezionamento)
- Fotografie (Nessun altro risultato corrispondente a questo perfezionamento)
- Mappe (Nessun altro risultato corrispondente a questo perfezionamento)
- Manoscritti e Collezionismo cartaceo (Nessun altro risultato corrispondente a questo perfezionamento)
Condizioni Maggiori informazioni
- Nuovo (32)
- Come nuovo, Ottimo o Quasi ottimo (6)
- Molto buono o Buono (Nessun altro risultato corrispondente a questo perfezionamento)
- Discreto o Mediocre (Nessun altro risultato corrispondente a questo perfezionamento)
- Come descritto (1)
Legatura
Ulteriori caratteristiche
- Prima ed. (Nessun altro risultato corrispondente a questo perfezionamento)
- Copia autograf. (Nessun altro risultato corrispondente a questo perfezionamento)
- Sovracoperta (Nessun altro risultato corrispondente a questo perfezionamento)
- Con foto (7)
- Non Print on Demand (22)
Lingua (1)
Spedizione gratuita
Paese del venditore
Valutazione venditore
-
Artificial Neural Networks And Evolutionary Computation In Remote Sensing
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 53,32
Spedizione EUR 2,32
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing (Hardback or Cased Book)
Da: BargainBookStores, Grand Rapids, MI, U.S.A.
Valutazione del venditore 5 su 5 stelle
Hardback or Cased Book. Condizione: New. Artificial Neural Networks and Evolutionary Computation in Remote Sensing. Book.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: California Books, Miami, FL, U.S.A.
Valutazione del venditore 4 su 5 stelle
EUR 57,82
Spedizione gratuita
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Artificial Neural Networks And Evolutionary Computation In Remote Sensing
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 55,83
Spedizione EUR 2,32
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 57,75
Spedizione EUR 14,02
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
-
Artificial Neural Networks And Evolutionary Computation In Remote Sensing
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 55,71
Spedizione EUR 17,56
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Artificial Neural Networks And Evolutionary Computation In Remote Sensing
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 63,63
Spedizione EUR 17,56
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
-
Classification Methods for Remotely Sensed Data
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 4 su 5 stelle
EUR 86,41
Spedizione EUR 7,61
Spedito da Regno Unito a U.S.A.Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
-
Classification Methods for Remotely Sensed Data
Da: Biblios, Frankfurt am main, HESSE, Germania
Valutazione del venditore 4 su 5 stelle
EUR 99,11
Spedizione EUR 9,95
Spedito da Germania a U.S.A.Quantità: 3 disponibili
Aggiungi al carrelloCondizione: New.
-
Classification Methods for Remotely Sensed Data
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New.
-
Classification Methods for Remotely Sensed Data
Da: Books From California, Simi Valley, CA, U.S.A.
Valutazione del venditore 4 su 5 stelle
hardcover. Condizione: Fine.
-
EUR 50,03
Spedizione EUR 105,00
Spedito da Germania a U.S.A.Quantità: 2 disponibili
Aggiungi al carrelloCondizione: Sehr gut. Zustand: Sehr gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
-
EUR 51,63
Spedizione EUR 105,00
Spedito da Germania a U.S.A.Quantità: 2 disponibili
Aggiungi al carrelloCondizione: Hervorragend. Zustand: Hervorragend | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: Mispah books, Redhill, SURRE, Regno Unito
Valutazione del venditore 4 su 5 stelle
EUR 142,27
Spedizione EUR 29,27
Spedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Aggiungi al carrelloHardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
-
Classification Methods for Remotely Sensed Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 190,81
Spedizione EUR 2,32
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
-
Classification Methods for Remotely Sensed Data
Da: GreatBookPrices, Columbia, MD, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 230,20
Spedizione EUR 2,32
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Classification Methods for Remotely Sensed Data
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. 3rd edition NO-PA16APR2015-KAP.
-
Classification Methods for Remotely Sensed Data
Da: California Books, Miami, FL, U.S.A.
Valutazione del venditore 4 su 5 stelle
EUR 240,31
Spedizione gratuita
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Classification Methods for Remotely Sensed Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 232,94
Spedizione EUR 17,56
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
-
Classification Methods for Remotely Sensed Data
Da: Ria Christie Collections, Uxbridge, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 241,83
Spedizione EUR 14,02
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New. In.
-
Classification Methods for Remotely Sensed Data
Da: GreatBookPricesUK, Woodford Green, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 241,82
Spedizione EUR 17,56
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
-
Classification Methods for Remotely Sensed Data
Da: Revaluation Books, Exeter, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 318,23
Spedizione EUR 14,63
Spedito da Regno Unito a U.S.A.Quantità: 2 disponibili
Aggiungi al carrelloHardcover. Condizione: Brand New. 3rd edition. 520 pages. 10.00x7.00x10.00 inches. In Stock.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: PBShop.store US, Wood Dale, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
EUR 61,01
Spedizione gratuita
Spedito in U.S.A.Quantità: Più di 20 disponibili
Aggiungi al carrelloHRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 55,72
Spedizione EUR 6,87
Spedito da Regno Unito a U.S.A.Quantità: Più di 20 disponibili
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.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: Majestic Books, Hounslow, Regno Unito
Valutazione del venditore 4 su 5 stelle
EUR 74,95
Spedizione EUR 7,61
Spedito da Regno Unito a U.S.A.Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. Print on Demand pp. 256.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: Books Puddle, New York, NY, U.S.A.
Valutazione del venditore 4 su 5 stelle
Condizione: New. Print on Demand pp. 256.
-
Artificial Neural Networks and Evolutionary Computation in Remote Sensing
Da: Biblios, Frankfurt am main, HESSE, Germania
Valutazione del venditore 4 su 5 stelle
EUR 74,75
Spedizione EUR 9,95
Spedito da Germania a U.S.A.Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. PRINT ON DEMAND pp. 256.
-
Classification Methods for Remotely Sensed Data (Paperback)
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032573953 ISBN 13: 9781032573953
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Valutazione del venditore 5 su 5 stelle
Paperback. Condizione: new. Paperback. The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods.New in this edition:Provides comprehensive background on the theory of deep learning and its application to remote sensing data.Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications.Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies.Discusses the methods used for explaining inherent structures and weighing the features of ML and AI algorithms that are critical for explaining the robustness of the models.This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc. The new edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data, and presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
-
Classification Methods for Remotely Sensed Data (Paperback)
Lingua: Inglese
Editore: Taylor & Francis Ltd, London, 2026
ISBN 10: 1032573953 ISBN 13: 9781032573953
Da: CitiRetail, Stevenage, Regno Unito
Valutazione del venditore 5 su 5 stelle
EUR 96,45
Spedizione EUR 43,31
Spedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods.New in this edition:Provides comprehensive background on the theory of deep learning and its application to remote sensing data.Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications.Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies.Discusses the methods used for explaining inherent structures and weighing the features of ML and AI algorithms that are critical for explaining the robustness of the models.This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc. The new edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data, and presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
-
EUR 62,35
Spedizione EUR 72,60
Spedito da Germania a U.S.A.Quantità: 2 disponibili
Aggiungi al carrelloBuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial neural networks (ANNs) and evolutionary computation methods have been successfully applied in remote sensing applications since they offer unique advantages for the analysis of remotely-sensed images. ANNs are effective in finding underlying relationships and structures within multidimensional datasets. Thanks to new sensors, we have images with more spectral bands at higher spatial resolutions, which clearly recall big data problems. For this purpose, evolutionary algorithms become the best solution for analysis. This book includes eleven high-quality papers, selected after a careful reviewing process, addressing current remote sensing problems. In the chapters of the book, superstructural optimization was suggested for the optimal design of feedforward neural networks, CNN networks were deployed for a nanosatellite payload to select images eligible for transmission to ground, a new weight feature value convolutional neural network (WFCNN) was applied for fine remote sensing image segmentation and extracting improved land-use information, mask regional-convolutional neural networks (Mask R-CNN) was employed for extracting valley fill faces, state-of-the-art convolutional neural network (CNN)-based object detection models were applied to automatically detect airplanes and ships in VHR satellite images, a coarse-to-fine detection strategy was employed to detect ships at different sizes, and a deep quadruplet network (DQN) was proposed for hyperspectral image classification.
