Domain Adaptation and Representation Transfer / Lecture Notes in Computer Science Bd.14293 (PDF)
5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings
(Sprache: Englisch)
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...
The 16 full papers presented in this book were...
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Produktinformationen zu „Domain Adaptation and Representation Transfer / Lecture Notes in Computer Science Bd.14293 (PDF)“
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.
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.
Bibliographische Angaben
- 2023, 1st ed. 2024, 170 Seiten, Englisch
- Herausgegeben: Lisa Koch, M. Jorge Cardoso, Enzo Ferrante, Konstantinos Kamnitsas, Mobarakol Islam, Meirui Jiang, Nicola Rieke, Sotirios A. Tsaftaris, Dong Yang
- Verlag: Springer International Publishing
- ISBN-10: 3031458575
- ISBN-13: 9783031458576
- Erscheinungsdatum: 13.10.2023
Abhängig von Bildschirmgrösse und eingestellter Schriftgrösse kann die Seitenzahl auf Ihrem Lesegerät variieren.
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- Grösse: 20 MB
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