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Ajouter au panierEtat : New. pp. XIII, 212 86 illus., 67 illus. in color. 1 Edition NO-PA16APR2015-KAP.
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Langue: anglais
Edité par Springer-Nature New York Inc, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
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Ajouter au panierPaperback. Etat : Brand New. 228 pages. 9.25x6.10x0.94 inches. In Stock.
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Edité par Springer-Verlag New York Inc, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
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Langue: anglais
Edité par Springer International Publishing, Springer Nature Switzerland Sep 2020, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Ajouter au panierTaschenbuch. Etat : 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.
Langue: anglais
Edité par Springer International Publishing, Springer Nature Switzerland Okt 2019, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019.DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains.MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 272 pp. Englisch.
Langue: anglais
Edité par Springer International Publishing, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
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Ajouter au panierTaschenbuch. Etat : 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.
Langue: anglais
Edité par Springer International Publishing, Springer International Publishing, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains. MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection.
Langue: anglais
Edité par Springer International Publishing Sep 2020, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierTaschenbuch. Etat : 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.
Langue: anglais
Edité par Springer International Publishing Okt 2019, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains. MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection. 272 pp. Englisch.
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Ajouter au panierEtat : New. Print on Demand pp. XIII, 212 86 illus., 67 illus. in color.
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Ajouter au panierEtat : New. PRINT ON DEMAND pp. XIII, 212 86 illus., 67 illus. in color.
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Langue: anglais
Edité par Springer International Publishing, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
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Ajouter au panierEtat : 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.
Langue: anglais
Edité par Springer International Publishing, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
Vendeur : moluna, Greven, Allemagne
EUR 48,37
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Ajouter au panierEtat : 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 First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held.