Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data (e-bok)
Format
E-bok
Filformat
EPUB med LCP-kryptering (0.0 MB)
Om LCP-kryptering
Nedladdning
Kan laddas ned under 24 månader, dock max 6 gånger.
Språk
Engelska
Utgivningsdatum
2019-10-13
Förlag
Springer International Publishing
ISBN
9783030333911

Domain Adaptation and Representation Transfer and Medical Image Learning with Less Labels and Imperfect Data E-bok

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

E-bok (LCP),  Engelska, 2019-10-13
783
Läs i Bokus Reader för iOS och Android
Finns även som
Visa alla 1 format & utgåvor
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.
Visa hela texten

Kundrecensioner

Har du läst boken? Sätt ditt betyg »