Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning: Second MICCAI Workshop, DART 2020, and First MICCAI ... Vision, Pattern Recognition, and Graphics) - Tapa blanda

9783030605476: Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning: Second MICCAI Workshop, DART 2020, and First MICCAI ... Vision, Pattern Recognition, and Graphics)

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ISBN 10: 3030605477 ISBN 13: 9783030605476

Editorial: Springer, 2020

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This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic.

For DART 2020, 12 full papers were accepted from 18 submissions. They deal with methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings by making them robust and consistent across different domains.

For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases; where information privacy is a priority; where it is necessary to deliver strong guarantees on the amount and nature of private information that may be revealed by the model as a result of training; and where it's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task.

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EditorialSpringer
A�o de publicaci�n2020
ISBN 10 3030605477
ISBN 13 9783030605476
Encuadernaci�nTapa blanda
IdiomaIngl�s
N�mero de edici�n1
N�mero de p�ginas228
EditorAlbarqouni Shadi, Bakas Spyridon, Kamnitsas Konstantinos, Cardoso M. Jorge, Landman Bennett, Li Wenqi, Milletari Fausto, Rieke Nicola, Roth Holger
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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning: Second Miccai Workshop, Dart 2020, and First Miccai Worksho

Publicado por Springer, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

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Paperback. Condici�n: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 0.72. N� de ref. del art�culo: G3030605477I4N00

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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning

Shadi Albarqouni

Publicado por Springer International Publishing Sep 2020, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania

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Taschenbuch. Condici�n: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic.For DART 2020, 12 full papers were accepted from 18 submissions. They deal withmethodological advancements and ideas thatcan improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings bymaking them robust and consistent across different domains.For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement andpractical ideas about machine learning applied to problems where data cannot be stored in centralizeddatabases; where information privacy is a priority; where it is necessary to deliver strong guarantees on theamount and nature of private information that may be revealed by the model as a result of training; and whereit's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task. 228 pp. Englisch. N� de ref. del art�culo: 9783030605476

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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning : Second MICCAI Workshop, DART 2020, and First MICCAI Workshop, DCL 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4�8, 2020, Proceedings

Shadi Albarqouni

Publicado por Springer International Publishing, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

Nuevo Taschenbuch

Librería: AHA-BUCH GmbH, Einbeck, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic.For DART 2020, 12 full papers were accepted from 18 submissions. They deal withmethodological advancements and ideas thatcan improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings bymaking them robust and consistent across different domains.For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement andpractical ideas about machine learning applied to problems where data cannot be stored in centralizeddatabases; where information privacy is a priority; where it is necessary to deliver strong guarantees on theamount and nature of private information that may be revealed by the model as a result of training; and whereit's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task. N� de ref. del art�culo: 9783030605476

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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning (Image Processing, Computer Vision, Pattern Recognition, and Graphics)

Publicado por Springer, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

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Condici�n: New. In. N� de ref. del art�culo: ria9783030605476_new

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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning

Publicado por Springer International Publishing, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

Nuevo Tapa blanda

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Librería: moluna, Greven, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Condici�n: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2. N� de ref. del art�culo: 403572125

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Domain Adaptation and Representation Transfer, and Distributed and Collaborative Learning

Shadi Albarqouni

Publicado por Springer International Publishing, Springer Nature Switzerland Sep 2020, 2020

ISBN 10: 3030605477 ISBN 13: 9783030605476

Nuevo Taschenbuch

Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania

Calificaci�n del vendedor: 5 de 5 estrellas

Taschenbuch. Condici�n: Neu. Neuware -This book constitutes the refereed proceedings of the Second MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2020, and the First MICCAI Workshop on Distributed and Collaborative Learning, DCL 2020, held in conjunction with MICCAI 2020 in October 2020. The conference was planned to take place in Lima, Peru, but changed to an online format due to the Coronavirus pandemic.For DART 2020, 12 full papers were accepted from 18 submissions. They deal with methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical settings by making them robust and consistent across different domains.For DCL 2020, the 8 papers included in this book were accepted from a total of 12 submissions. They focus on the comparison, evaluation and discussion of methodological advancement and practical ideas about machine learning applied to problems where data cannot be stored in centralized databases; where information privacy is a priority; where it is necessary to deliver strong guarantees on the amount and nature of private information that may be revealed by the model as a result of training; and where it's necessary to orchestrate, manage and direct clusters of nodes participating in the same learning task.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. N� de ref. del art�culo: 9783030605476

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