Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data - First MICCAI Workshop, DART 2019, and First International Workshop, MIL3ID 2019, Shenzhen, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13 and 17, 2019, Proceedings (Paperback, 1st ed. 2019)


This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains. MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection.

R1,557

Or split into 4x interest-free payments of 25% on orders over R50
Learn more

Discovery Miles15570
Mobicred@R146pm x 12* Mobicred Info
Free Delivery
Delivery AdviceShips in 10 - 15 working days


Toggle WishListAdd to wish list
Review this Item

Product Description

This book constitutes the refereed proceedings of the First MICCAI Workshop on Domain Adaptation and Representation Transfer, DART 2019, and the First International Workshop on Medical Image Learning with Less Labels and Imperfect Data, MIL3ID 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. DART 2019 accepted 12 papers for publication out of 18 submissions. The papers deal with methodological advancements and ideas that can improve the applicability of machine learning and deep learning approaches to clinical settings by making them robust and consistent across different domains. MIL3ID accepted 16 papers out of 43 submissions for publication, dealing with best practices in medical image learning with label scarcity and data imperfection.

Customer Reviews

No reviews or ratings yet - be the first to create one!

Product Details

General

Imprint

Springer Nature Switzerland AG

Country of origin

Switzerland

Series

Lecture Notes in Computer Science, 11795

Release date

October 2019

Availability

Expected to ship within 10 - 15 working days

First published

2019

Editors

, , , , , , , , ,

Dimensions

235 x 155mm (L x W)

Format

Paperback

Pages

254

Edition

1st ed. 2019

ISBN-13

978-3-03-033390-4

Barcode

9783030333904

Categories

LSN

3-03-033390-6



Trending On Loot