株式会社極東書店トップ ＞ 商品一覧 ＞ Domain Adaptation and Representation Transfer: 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. 1st ed. 2024
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Domain Adaptation and Representation Transfer: 5th MICCAI Workshop, DART 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings. 1st ed. 2024
・ISBN 978-3-031-45856-9 paper EUR 49.99
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| 著者・編者 | Koch, Lisa / Cardoso, M. Jorge / Ferrante, Enzo / Kamnitsas, Konstantinos / Islam, Mobarakol / Jiang, Meirui / Rieke, Nicola / Tsaftaris, Sotirios A. / Yang, Dong (eds.), |
|---|---|
| シリーズ | (Lecture Notes in Computer Science) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2023 |
| ページ数 | 170 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A01-79966＞ |
解説
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.