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
Harnessing the Potential of Advanced Large Vision Models to..:
, In:
2024 22nd International Conference on Optical Communications and Networks (ICOCN)
,
Liang, Dunyou
;
Chang, Xin
;
Peng, Feng
... - p. 1-3 , 2024
Link:
https://doi.org/10.1109/ICOCN63276.2024.10647230
RT T1 <cTitle>2024 22nd International Conference on Optical Communications and Networks (ICOCN)</cTitle>: T1 <Title>Harnessing the Potential of Advanced Large Vision Models to Enhance the Detection of Optoelectronic Imaging Signals</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10647230&Exemplar=1&LAN=DE A1 Liang, Dunyou A1 Chang, Xin A1 Peng, Feng A1 Wu, Bing A1 Cui, Xiaojun A1 Zuo, Xin A1 Ma, JianChao A1 Zhang, Guoyu YR 2024 SN 2771-3059 K1 Measurement K1 Image segmentation K1 Analytical models K1 Visualization K1 Training data K1 Data models K1 Optical fiber communication K1 Large Vision Models K1 Optoelectronic imaging K1 Deep learning SP 1 OP 3 LK http://dx.doi.org/https://doi.org/10.1109/ICOCN63276.2024.10647230 DO https://doi.org/10.1109/ICOCN63276.2024.10647230 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
