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
Efficient Training of 3D Unrolled Neural Networks for MRI R..:
, In:
2021 55th Asilomar Conference on Signals, Systems, and Computers
,
Deng, Zilin
;
Yaman, Burhaneddin
;
Zhang, Chi
.. - p. 886-889 , 2021
Link:
https://doi.org/10.1109/IEEECONF53345.2021.9723247
RT T1
2021 55th Asilomar Conference on Signals, Systems, and Computers
: T1
Efficient Training of 3D Unrolled Neural Networks for MRI Reconstruction Using Small Databases
UL https://suche.suub.uni-bremen.de/peid=ieee-9723247&Exemplar=1&LAN=DE A1 Deng, Zilin A1 Yaman, Burhaneddin A1 Zhang, Chi A1 Moeller, Steen A1 Akcakaya, Mehmet YR 2021 SN 2576-2303 K1 Training K1 Deep learning K1 Three-dimensional displays K1 Image resolution K1 Databases K1 Magnetic resonance imaging K1 Neural networks K1 3D processing K1 deep learning K1 network training K1 algorithm unrolling K1 MRI SP 886 OP 889 LK http://dx.doi.org/https://doi.org/10.1109/IEEECONF53345.2021.9723247 DO https://doi.org/10.1109/IEEECONF53345.2021.9723247 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)