Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data (Image Processing, Computer Vision, Pattern Recognition, and Graphics)
ISBN 10: 3030333906 ISBN 13: 9783030333904
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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.
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Title: Domain Adaptation and Representation ...
Publisher: Springer
Publication Date: 2019
Binding: Soft cover
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data
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Condition: 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. Seller Inventory # 385699843
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data (Image Processing, Computer Vision, Pattern Recognition, and Graphics)
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data | First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings
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Taschenbuch. Condition: Neu. Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data | First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings | Qian Wang (u. a.) | Taschenbuch | xvii | Englisch | 2019 | Springer | EAN 9783030333904 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 117437914
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Domain Adaptation and Representation Transfer and Medical Image Learning With Less Labels and Imperfect Data : First Miccai Workshop, Dart 2019, and First International Workshop, Mil3id 2019, Shenzhen, Held in Conjunction With Miccai 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data
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Springer International Publishing, Springer Nature Switzerland Okt 2019, 2019
ISBN 10: 3030333906
ISBN 13: 9783030333904
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Taschenbuch. Condition: 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. Seller Inventory # 9783030333904
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data : First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings
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ISBN 13: 9783030333904
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Taschenbuch. Condition: 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. Seller Inventory # 9783030333904
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Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data
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Springer International Publishing Okt 2019, 2019
ISBN 10: 3030333906
ISBN 13: 9783030333904
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Taschenbuch. Condition: 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. Seller Inventory # 9783030333904
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