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
Automated Pavement Crack Detection with Deep Learning Metho..:
Gong, Haitao
;
Tešić, Jelena
;
Tao, Jueqiang
..
Transportation Research Record: Journal of the Transportation Research Board. 2677 (2023) 10 - p. 311-323 , 2023
Link:
https://doi.org/10.1177/03611981231161358
RT Journal T1 <Title>Automated Pavement Crack Detection with Deep Learning Methods: What Are the Main Factors and How to Improve the Performance?</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1177_03611981231161358&Exemplar=1&LAN=DE A1 Gong, Haitao A1 Tešić, Jelena A1 Tao, Jueqiang A1 Luo, Xiaohua A1 Wang, Feng PB SAGE Publications YR 2023 SN 0361-1981 SN 2169-4052 JF Transportation Research Record: Journal of the Transportation Research Board VO 2677 IS 10 SP 311 OP 323 LK http://dx.doi.org/https://doi.org/10.1177/03611981231161358 DO https://doi.org/10.1177/03611981231161358 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
