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Interpretable and Annotation-efficient Learning for Medical Image Computing :...

Description: 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, Paperback by Cardoso, Jaime (EDT); Van Nguyen, Hien (EDT); Heller, Nicholas (EDT); Abreu, Pedro Henriques (EDT); Isgum, Ivana (EDT), ISBN 3030611655, ISBN-13 9783030611651, Brand New, Free shipping in the US This book constitutes the refereed joint proceedings of the Third International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, the Second International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2020, and the 5th International Workshop on Large-scale Annotation of Biomedical data and Expert Label Synthesis, LABELS 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The 8 full papers presented at iMIMIC 2020, 11 full papers to MIL3ID 2020, and the 10 full papers presented at LABELS 2020 were carefully reviewed and selected from 16 submissions to iMIMIC, 28 to MIL3ID, and 12 submissions to LABELS. The iMIMIC papers focus on introducing the challenges and opportunities related to the topic of interpretability of machine learning systems in the context of medical imaging and computer assisted intervention. MIL3ID deals with best practices in medical image learning with label scarcity and data imperfection. The LABELS papers present a variety of approaches for dealing with a limited number of labels, from semi-supervised learning to crowdsourcing.

Price: 65.98 USD

Location: Jessup, Maryland

End Time: 2024-11-25T17:12:58.000Z

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Interpretable and Annotation-efficient Learning for Medical Image Computing :...

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Book Title: Interpretable and Annotation-efficient Learning for Medical Image

Number of Pages: Xvii, 292 Pages

Publication Name: 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

Language: English

Publisher: Springer International Publishing A&G

Publication Year: 2020

Subject: Intelligence (Ai) & Semantics, Computer Vision & Pattern Recognition, Enterprise Applications / General

Type: Textbook

Item Weight: 17.1 Oz

Item Length: 9.3 in

Author: Hien Van Nguyen

Subject Area: Computers

Series: Lecture Notes in Computer Science Ser.

Item Width: 6.1 in

Format: Trade Paperback

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