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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Seiten: 180 | Sprache: Englisch | Produktart: Bücher.
Edité par Springer Nature Switzerland, 2022
ISBN 10 : 3031168518 ISBN 13 : 9783031168512
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Ajouter au panierEtat : Hervorragend. Zustand: Hervorragend | Seiten: 160 | Sprache: Englisch | Produktart: Bücher.
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Ajouter au panierPaperback. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 0.72.
Edité par Springer International Publishing AG, 2022
ISBN 10 : 3031168518 ISBN 13 : 9783031168512
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Edité par Springer, Berlin|Springer Nature Switzerland|Springer, 2022
ISBN 10 : 3031168518 ISBN 13 : 9783031168512
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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.
Edité par Springer International Publishing, Springer International Publishing, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
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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.
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Edité par Springer International Publishing, Springer Nature Switzerland Sep 2020, 2020
ISBN 10 : 3030605477 ISBN 13 : 9783030605476
Langue: anglais
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EUR 53,49
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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.
Edité par Springer International Publishing, Springer Nature Switzerland Okt 2019, 2019
ISBN 10 : 3030333906 ISBN 13 : 9783030333904
Langue: anglais
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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.
Edité par Springer Nature Switzerland, 2022
ISBN 10 : 3031168518 ISBN 13 : 9783031168512
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022.DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.
Edité par Springer Nature Switzerland, Springer International Publishing, 2023
ISBN 10 : 3031458567 ISBN 13 : 9783031458569
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Ajouter au panierTaschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.The 16 full papers presented in this book were carefully reviewed and selected from 32 submissions. They discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.
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Edité par Springer Nature Switzerland, Springer Nature Switzerland Okt 2023, 2023
ISBN 10 : 3031458567 ISBN 13 : 9783031458569
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -This book constitutes the refereed proceedings of the 5th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2023, which was held in conjunction with MICCAI 2023, in October 2023.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 180 pp. Englisch.
Edité par Springer Nature Switzerland, Springer International Publishing Sep 2022, 2022
ISBN 10 : 3031168518 ISBN 13 : 9783031168512
Langue: anglais
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EUR 58,84
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -This book constitutes the refereed proceedings of the 4th MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2022, held in conjunction with MICCAI 2022, in September 2022. DART 2022 accepted 13 papers from the 25 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch.
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Edité par Springer International Publishing, 2021
ISBN 10 : 3030877213 ISBN 13 : 9783030877217
Langue: anglais
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 Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.DART 2021 accepted 13 papers from the 21 submissions received. The workshop aims at creating a discussion forum to compare, evaluate, and discuss methodological advancements and ideas that can improve the applicability of machine learning (ML)/deep learning (DL) approaches to clinical setting by making them robust and consistent across different domains. For FAIR 2021, 10 papers from 17 submissions were accepted for publication. They focus on Image-to-Image Translation particularly for low-dose or low-resolution settings; Model Compactness and Compression; Domain Adaptation and Transfer Learning; Active, Continual and Meta-Learning.
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Edité par Springer International Publishing, Springer Nature Switzerland Sep 2021, 2021
ISBN 10 : 3030877213 ISBN 13 : 9783030877217
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : Neu. Neuware -This book constitutes the refereed proceedings of the Third MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2021, and the First MICCAI Workshop on Affordable Healthcare and AI for Resource Diverse Global Health, FAIR 2021, held in conjunction with MICCAI 2021, in September/October 2021. The workshops were planned to take place in Strasbourg, France, but were held virtually due to the COVID-19 pandemic.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 280 pp. Englisch.
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