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
Application of deep metric learning model to microscope ima..:
Kimura, Yoshiki
;
Matsumoto, Tetsuya
;
Yamaguchi, Tomoki
Journal of Radioanalytical and Nuclear Chemistry. 333 (2024) 7 - p. 3541-3551 , 2024
Link:
https://doi.org/10.1007/s10967-023-09300-w
RT Journal T1 <Title>Application of deep metric learning model to microscope image analysis for the determination of UOC samples in nuclear forensics analysis</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_s10967-023-09300-w&Exemplar=1&LAN=DE A1 Kimura, Yoshiki A1 Matsumoto, Tetsuya A1 Yamaguchi, Tomoki PB Springer Science and Business Media LLC YR 2024 SN 0236-5731 SN 1588-2780 JF Journal of Radioanalytical and Nuclear Chemistry VO 333 IS 7 SP 3541 OP 3551 LK http://dx.doi.org/https://doi.org/10.1007/s10967-023-09300-w DO https://doi.org/10.1007/s10967-023-09300-w SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
