I agree that this site is using cookies. You can find further informations
here
.
X
Login
Merkliste (
0
)
Home
About us
Home About us
Our history
Profile
Press & public relations
Friends
The library in figures
Exhibitions
Projects
Training, internships, careers
Films
Services & Information
Home Services & Information
Lending and interlibrary loans
Returns and renewals
Training and library tours
My Account
Library cards
New to the library?
Download Information
Opening hours
Learning spaces
PC, WLAN, copy, scan and print
Catalogs and collections
Home Catalogs and Collections
Rare books and manuscripts
Digital collections
Subject Areas
Our sites
Home Our sites
Central Library
Law Library (Juridicum)
BB Business and Economics (BB11)
BB Physics and Electrical Engineering
TB Engineering and Social Sciences
TB Economics and Nautical Sciences
TB Music
TB Art & Design
TB Bremerhaven
Contact the library
Home Contact the library
Staff Directory
Open access & publishing
Home Open access & publishing
Reference management: Citavi & RefWorks
Publishing documents
Open Access in Bremen
zur Desktop-Version
Toggle navigation
Merkliste
1 Ergebnisse
1
IDAA-NET: An Image Domain Adaptive Alignment Network for Un..:
, In:
2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
,
Geng, Haixiao
;
Fan, Jingfan
;
Yuan, Yujia
... - p. 1925-1928 , 2023
Link:
https://doi.org/10.1109/BIBM58861.2023.10385431
RT T1 <cTitle>2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)</cTitle>: T1 <Title>IDAA-NET: An Image Domain Adaptive Alignment Network for Unsupervised Liver Vessel Segmentation from CTA Images</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10385431&Exemplar=1&LAN=DE A1 Geng, Haixiao A1 Fan, Jingfan A1 Yuan, Yujia A1 Ai, Danni A1 Duan, Feng A1 Yang, Jian YR 2023 SN 2156-1133 K1 Training K1 Image segmentation K1 Adaptive systems K1 Three-dimensional displays K1 Liver diseases K1 Supervised learning K1 Predictive models K1 CTA image K1 MRA image K1 Vessel segmentation K1 Unsupervised learning K1 Adversarial learning SP 1925 OP 1928 LK http://dx.doi.org/https://doi.org/10.1109/BIBM58861.2023.10385431 DO https://doi.org/10.1109/BIBM58861.2023.10385431 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
