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Domain Adaptation and Representation Transfer - 4th MICCAI Workshop, DART 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings (Paperback, 1st ed. 2022)
Konstantinos Kamnitsas, Lisa Koch, Mobarakol Islam, Ziyue Xu, Jorge Cardoso, …
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R1,494
Discovery Miles 14 940
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Ships in 12 - 19 working days
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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.
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Domain Adaptation and Representation Transfer, and Affordable Healthcare and AI for Resource Diverse Global Health - Third MICCAI Workshop, DART 2021, and First MICCAI Workshop, FAIR 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27 and October 1, 2021, Proceedings (Paperback, 1st ed. 2021)
Shadi Albarqouni, M. Jorge Cardoso, Qi Dou, Konstantinos Kamnitsas, Bishesh Khanal, …
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R1,886
Discovery Miles 18 860
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Ships in 10 - 15 working days
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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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R391
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Discovery Miles 3 620
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