Christian F. Baumgartner | Akateeminen Kirjakauppa

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UNCERTAINTY FOR SAFE UTILIZATION OF MACHINE LEARNING IN MEDICAL IMAGING, AND GRAPHS IN BIOMEDICAL IMAGE ANALYSIS - SECOND INTERN

Carole H. Sudre; Hamid Fehri; Tal Arbel; Christian F. Baumgartner; Adrian Dalca; Ryutaro Tanno; Koen Van Leemput; Wells
Springer Nature Switzerland AG (2020)
Pehmeäkantinen kirja

49,60 €

UNCERTAINTY FOR SAFE UTILIZATION OF MACHINE LEARNING IN MEDICAL IMAGING : 4TH INTERNATIONAL WORKSHOP, UNSURE 2022, HELD IN CONJU

Carole H. Sudre (ed.); Christian F. Baumgartner (ed.); Adrian Dalca (ed.); Chen Qin (ed.); Ryutaro Tanno (ed.); Van Leemput
Springer (2022)
Pehmeäkantinen kirja

54,40 €

UNCERTAINTY FOR SAFE UTILIZATION OF MACHINE LEARNING IN MEDICAL IMAGING : 5TH INTERNATIONAL WORKSHOP, UNSURE 2023, HELD IN CONJU

Carole H. Sudre (ed.); Christian F. Baumgartner (ed.); Adrian Dalca (ed.); Raghav Mehta (ed.); Chen Qin (ed.); Willi Wells
Springer (2023)
Pehmeäkantinen kirja

57,30 €

Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Graphs in Biomedical Image Analysis - Second Intern

Carole H. Sudre, Hamid Fehri, Tal Arbel, Christian F. Baumgartner, Adrian Dalca, Ryutaro Tanno, Koen Van Leemput, Wells

49,60 €

Springer Nature Switzerland AG
Sivumäärä: 222 sivua
Asu: Pehmeäkantinen kirja
Painos: 1st ed. 2020
Julkaisuvuosi: 2020, 06.10.2020 (lisätietoa)
Kieli: Englanti
Tuotesarja: Image Processing, Computer Vision, Pattern Recognition, and Graphics

This book constitutes the refereed proceedings of the Second International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, UNSURE 2020, and the Third International Workshop on Graphs in Biomedical Image Analysis, GRAIL 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshops were held virtually due to the COVID-19 pandemic.For UNSURE 2020, 10 papers from 18 submissions were accepted for publication. They focus on developing awareness and encouraging research in the field of uncertainty modelling to enable safe implementation of machine learning tools in the clinical world.

GRAIL 2020 accepted 10 papers from the 12 submissions received. The workshop aims to bring together scientists that use and develop graph-based models for the analysis of biomedical images and to encourage the exploration of graph-based models for difficult clinical problems within a variety of biomedical imaging contexts.

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