Interpretable CNN Pruning for Preserving Scale-Covariant Features in Medical Imaging

This is a publication. If there is no link to the publication on this page, you can try the pre-formated search via the search engines listed on this page.

Authors: Mara Graziani, Thomas Lompech, Henning Müller, Adrien Depeursinge, Vincent Andrearczyk

Journal title: Interpretable and Annotation-Efficient Learning for Medical Image Computing - Third International Workshop, iMIMIC 2020, Second International Workshop, MIL3ID 2020, and 5th International Workshop, LABELS 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4–8, 2020, Proceedings

Journal number: 12446

Journal publisher: Springer International Publishing

Published year: 2020

Published pages: 23-32

DOI identifier: 10.1007/978-3-030-61166-8_3

ISBN: 978-3-030-61165-1