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
A Deep Learning-based ROV Surveillance System for Monitorin..:
, In:
2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)
,
Huang, Xiang-Rui
;
Huang, Guan-Zhi
;
Chen, Liang-Bi
- p. 1190-1191 , 2023
Link:
https://doi.org/10.1109/GCCE59613.2023.10315589
RT T1
2023 IEEE 12th Global Conference on Consumer Electronics (GCCE)
: T1
A Deep Learning-based ROV Surveillance System for Monitoring Illegal Fishing
UL https://suche.suub.uni-bremen.de/peid=ieee-10315589&Exemplar=1&LAN=DE A1 Huang, Xiang-Rui A1 Huang, Guan-Zhi A1 Chen, Liang-Bi YR 2023 SN 2693-0854 K1 Deep learning K1 Autonomous underwater vehicles K1 Computer vision K1 Surveillance K1 Real-time systems K1 Safety K1 Servers K1 AIoT K1 illegal fishing K1 deep learning SP 1190 OP 1191 LK http://dx.doi.org/https://doi.org/10.1109/GCCE59613.2023.10315589 DO https://doi.org/10.1109/GCCE59613.2023.10315589 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)