Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 60,00
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In den WarenkorbZustand: New. In.
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes Königreich
EUR 60,00
Anzahl: Mehr als 20 verfügbar
In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Springer-Nature New York Inc, 2020
ISBN 10: 3030605477 ISBN 13: 9783030605476
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 76,30
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In den WarenkorbPaperback. Zustand: Brand New. 228 pages. 9.25x6.10x0.94 inches. In Stock.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2019
ISBN 10: 3030333906 ISBN 13: 9783030333904
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 76,97
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In den WarenkorbPaperback. Zustand: Brand New. 274 pages. 9.25x6.10x0.67 inches. In Stock.
Zustand: New.
Anbieter: Kennys Bookstore, Olney, MD, USA
Zustand: New.
Sprache: Englisch
Verlag: Springer International Publishing, 2020
ISBN 10: 3030605477 ISBN 13: 9783030605476
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030333906 ISBN 13: 9783030333904
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: 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 | Lecture Notes in Computer Science | 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.