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
Identifying strong lenses with unsupervised machine learnin..:
Metcalf, Robert B
;
Dye, Simon
;
Aragón-Salamanca, Alfonso
...
Monthly Notices of the Royal Astronomical Society. 494 (2020) 3 - p. 3750-3765 , 2020
Link:
https://doi.org/10.1093/mnras/staa1015
RT Journal T1 <Title>Identifying strong lenses with unsupervised machine learning using convolutional autoencoder</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1093_mnras_staa1015&Exemplar=1&LAN=DE A1 Metcalf, Robert B A1 Dye, Simon A1 Aragón-Salamanca, Alfonso A1 Conselice, Christopher J A1 Li, Nan A1 Cheng, Ting-Yun PB Oxford University Press (OUP) YR 2020 SN 0035-8711 SN 1365-2966 JF Monthly Notices of the Royal Astronomical Society VO 494 IS 3 SP 3750 OP 3765 LK http://dx.doi.org/https://doi.org/10.1093/mnras/staa1015 DO https://doi.org/10.1093/mnras/staa1015 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
