Lingua: Inglese
Editore: Springer Nature Switzerland, 2022
ISBN 10: 3031167597 ISBN 13: 9783031167591
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
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Aggiungi al carrelloCondizione: Gut. Zustand: Gut | Seiten: 256 | Sprache: Englisch | Produktart: Bücher | This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Medical Image Learning with Limited and Noisy Data | First International Workshop, MILLanD 2022, Held in Conjunction with MICCAI 2022, Singapore, September 22, 2022, Proceedings | Ghada Zamzmi (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xi | Englisch | 2022 | Springer | EAN 9783031167591 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Da: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Print on demand title. Delivery takes 20-25 days.
Lingua: Inglese
Editore: Springer Nature Switzerland Sep 2022, 2022
ISBN 10: 3031167597 ISBN 13: 9783031167591
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data. 252 pp. Englisch.
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Lingua: Inglese
Editore: Springer, Berlin|Springer Nature Switzerland|Springer, 2022
ISBN 10: 3031167597 ISBN 13: 9783031167591
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Aggiungi al carrelloKartoniert / Broschiert. Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions .
Lingua: Inglese
Editore: Springer, Springer Sep 2022, 2022
ISBN 10: 3031167597 ISBN 13: 9783031167591
Da: buchversandmimpf2000, Emtmannsberg, BAYE, Germania
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book constitutes the proceedings of the First Workshop on Medical Image Learning with Limited and Noisy Data, MILLanD 2022, held in conjunction with MICCAI 2022. The conference was held in Singapore. For this workshop, 22 papers from 54 submissions were accepted for publication. They selected papers focus on the challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 256 pp. Englisch.