Fr. 89.00

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

English · Paperback / Softback

Shipping usually within 1 to 2 weeks (title will be printed to order)

Description

Read more

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.

List of contents

Uncertainty estimation and modelling.- Out of Distribution management and domain shift robustness.- Bayesian deep learning and uncertainty calibration.

Product details

Authors Carole H Sudre, Carole H. Sudre
Assisted by Christian F. Baumgartner (Editor), Adrian Dalca (Editor), Adrian Dalca et al (Editor), Christian F Baumgartner (Editor), Raghav Mehta (Editor), Raghav Mehta et al (Editor), Chen Qin (Editor), Carole H. Sudre (Editor), William M. Wells (Editor)
Publisher Springer, Berlin
 
Languages English
Product format Paperback / Softback
Released 27.10.2023
 
EAN 9783031443350
ISBN 978-3-0-3144335-0
No. of pages 220
Dimensions 155 mm x 12 mm x 235 mm
Illustrations XIII, 220 p. 58 illus., 54 illus. in color.
Series Lecture Notes in Computer Science
Subject Natural sciences, medicine, IT, technology > IT, data processing > IT

Customer reviews

No reviews have been written for this item yet. Write the first review and be helpful to other users when they decide on a purchase.

Write a review

Thumbs up or thumbs down? Write your own review.

For messages to CeDe.ch please use the contact form.

The input fields marked * are obligatory

By submitting this form you agree to our data privacy statement.