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
Domain Adaptation Assisted Stochastic Parallel Gradient Des..:
, In:
2023 6th International Conference on Robotics, Control and Automation Engineering (RCAE)
,
Zhang, Zhengxu
;
Mi, Xianya
;
Zhang, Xiaochuan
.. - p. 224-228 , 2023
Link:
https://doi.org/10.1109/RCAE59706.2023.10398788
RT T1 <cTitle>2023 6th International Conference on Robotics, Control and Automation Engineering (RCAE)</cTitle>: T1 <Title>Domain Adaptation Assisted Stochastic Parallel Gradient Descent for Coherent Beam Combination: From Simulation to Simulated Reality</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10398788&Exemplar=1&LAN=DE A1 Zhang, Zhengxu A1 Mi, Xianya A1 Zhang, Xiaochuan A1 Tan, Yi A1 Ren, Xiaoguang YR 2023 K1 Deep learning K1 Training K1 Phased arrays K1 Adaptation models K1 Computational modeling K1 Stochastic processes K1 Phase control K1 coherent beam combination K1 unsupervised domain adaptation K1 deep learning K1 generalization SP 224 OP 228 LK http://dx.doi.org/https://doi.org/10.1109/RCAE59706.2023.10398788 DO https://doi.org/10.1109/RCAE59706.2023.10398788 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
