Domain Adaptation and Representation Transfer / Lecture Notes in Computer Science Bd.13542 (PDF)
4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings
(Sprache: Englisch)
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....
DART 2022 accepted 13 papers from the 25 submissions received....
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Produktinformationen zu „Domain Adaptation and Representation Transfer / Lecture Notes in Computer Science Bd.13542 (PDF)“
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.
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.
Bibliographische Angaben
- 2022, 1st ed. 2022, 147 Seiten, Englisch
- Herausgegeben: Konstantinos Kamnitsas, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, Qi Dou, Nicola Rieke, Sotirios Tsaftaris
- Verlag: Springer International Publishing
- ISBN-10: 3031168526
- ISBN-13: 9783031168529
- Erscheinungsdatum: 19.09.2022
Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Größe: 20 MB
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Englisch
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