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
AdaBrowse: Adaptive Video Browser for Efficient Continuous ..:
, In:
Proceedings of the 31st ACM International Conference on Multimedia
,
Hu, Lianyu
;
Gao, Liqing
;
Liu, Zekang
.. - p. 709-718 , 2023
Link:
https://dl.acm.org/doi/10.1145/3581783.3611745
RT T1 <cTitle>Proceedings of the 31st ACM International Conference on Multimedia</cTitle>: T1 <Title>AdaBrowse: Adaptive Video Browser for Efficient Continuous Sign Language Recognition</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3611745&Exemplar=1&LAN=DE A1 Hu, Lianyu A1 Gao, Liqing A1 Liu, Zekang A1 Pun, Chi-Man A1 Feng, Wei PB ACM YR 2023 K1 continuous sign language recognition K1 efficient inference K1 feature redundancy K1 Computing methodologies K1 Artificial intelligence K1 Computer vision K1 Computer vision tasks K1 Activity recognition and understanding K1 Machine learning K1 Machine learning approaches K1 Neural networks K1 Learning paradigms K1 Supervised learning SP 709 OP 718 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3581783.3611745 DO https://dl.acm.org/doi/10.1145/3581783.3611745 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
