Da: PlumCircle, West Mifflin, PA, U.S.A.
paperback. Condizione: Very Good. Publisher overstock. May have remainder mark / minor shelfwear. 99% of orders arrive in 4-10 days. Discounted shipping on multiple books.
Da: Majestic Books, Hounslow, Regno Unito
EUR 127,87
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 139,68
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Aggiungi al carrelloCondizione: New.
Condizione: New.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 137,96
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 143,37
Quantità: 3 disponibili
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Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 163,56
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 155,37
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 152,45
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 169,27
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, US, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 194,51
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Aggiungi al carrelloPaperback. Condizione: New. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
EUR 153,44
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Aggiungi al carrelloCondizione: New. Presents the specific challenges in developing and deploying FL to medical imagingExplains the tools for developing or using FLPresents the state-of-the-art algorithms in the field with open source software on GithubGives .
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, US, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
Da: Rarewaves.com UK, London, Regno Unito
EUR 183,11
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Aggiungi al carrelloPaperback. Condizione: New. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc Jun 2025, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 213,53
Quantità: 2 disponibili
Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware - Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 115,50
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Aggiungi al carrelloCondizione: new. Questo è un articolo print on demand.
Da: Revaluation Books, Exeter, Regno Unito
EUR 125,49
Quantità: 2 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 260 pages. 9.25x7.50x9.22 inches. In Stock. This item is printed on demand.
Lingua: Inglese
Editore: Elsevier Science Publishing Co Inc, San Diego, 2025
ISBN 10: 0443236410 ISBN 13: 9780443236419
Da: CitiRetail, Stevenage, Regno Unito
EUR 128,16
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: new. Paperback. Federated Learning for Medical Imaging: Principles, Algorithms, and Applications gives a deep understanding of the technology of federated learning (FL), the architecture of a federated system, and the algorithms for FL. It shows how FL allows multiple medical institutes to collaboratively train and use a precise machine learning (ML) model without sharing private medical data via practical implantation guidance. The book includes real-world case studies and applications of FL, demonstrating how this technology can be used to solve complex problems in medical imaging. The book also provides an understanding of the challenges and limitations of FL for medical imaging, including issues related to data and device heterogeneity, privacy concerns, synchronization and communication, etc.This book is a complete resource for computer scientists and engineers, as well as clinicians and medical care policy makers, wanting to learn about the application of federated learning to medical imaging. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.