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
Line-based deep learning method for tree branch detection f..:
Silva, Rodrigo
;
Junior, José Marcato
;
Almeida, Laisa
...
International Journal of Applied Earth Observation and Geoinformation. 110 (2022) - p. 102759 , 2022
Link:
https://doi.org/10.1016/j.jag.2022.102759
RT Journal T1
Line-based deep learning method for tree branch detection from digital images
UL https://suche.suub.uni-bremen.de/peid=cr-10.1016_j.jag.2022.102759&Exemplar=1&LAN=DE A1 Silva, Rodrigo A1 Junior, José Marcato A1 Almeida, Laisa A1 Gonçalves, Diogo A1 Zamboni, Pedro A1 Fernandes, Vanessa A1 Silva, Jonathan A1 Matsubara, Edson A1 Batista, Edson A1 Ma, Lingfei A1 Li, Jonathan A1 Gonçalves, Wesley PB Elsevier BV YR 2022 SN 1569-8432 JF International Journal of Applied Earth Observation and Geoinformation VO 110 SP 102759 LK http://dx.doi.org/https://doi.org/10.1016/j.jag.2022.102759 DO https://doi.org/10.1016/j.jag.2022.102759 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)