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Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 7th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2025, held in conjunction with MICCAI 2025, in Daejon, South Korea, on September 27, 2025.The 22 full papers included in this book were carefully reviewed and selected from 33 submissions. They were organized in topical sections as follows: Risk management, uncertainty interpretation and visualisation; domain shift and out-of-distribution management; uncertainty calibration; and uncertainty modelling and estimation, Bayesian deep learning.

Taschenbuch. Zustand: Neu. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging | 7th International Workshop, UNSURE 2025, Held in Conjunction with MICCAI 2025, Daejeon, South Korea, September 27, 2025, Proceedings | Carole H. Sudre (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xi | Englisch | 2025 | Springer | EAN 9783032065926 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023.For this workshop, 21 papers from 32 submissions were accepted for publication.The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the refereed proceedings of the 6th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2024, held in conjunction with MICCAI 2024, Marrakesh, Morocco, on October 10, 2024.The 20 full papers presented in this book were carefully reviewed and selected from 28 submissions. They are organized in the following topical sections: annotation uncertainty; clinical implementation of uncertainty modelling and risk management in clinical pipelines; out of distribution and domain shift identification and management; uncertainty modelling and estimation.

Taschenbuch. Zustand: Neu. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging | 6th International Workshop, UNSURE 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings | Carole H. Sudre (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xi | Englisch | 2024 | Springer | EAN 9783031731570 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Uncertainty for Safe Utilization of Machine Learning in Medical Imaging | 5th International Workshop, UNSURE 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023, Proceedings | Carole H. Sudre (u. a.) | Taschenbuch | Lecture Notes in Computer Science | xiii | Englisch | 2023 | Springer | EAN 9783031443350 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book constitutes the refereed proceedings of the 5th Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2023, held in conjunction with MICCAI 2023 in Vancouver, Canada, in October 2023. For this workshop, 21 papers from 32 submissions were accepted for publication. The accepted papers cover the fields of uncertainty estimation and modeling, as well as out of distribution management, domain shift robustness, Bayesian deep learning and uncertainty calibration.