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
Detectability of pulmonary nodules by deep learning: result..:
Li, Qiong
;
Li, Qing-chu
;
Cao, Rui-ting
...
Chinese Journal of Academic Radiology. 2 (2019) 1-2 - p. 1-12 , 2019
Link:
https://doi.org/10.1007/s42058-019-00015-0
RT Journal T1
Detectability of pulmonary nodules by deep learning: results from a phantom study
UL https://suche.suub.uni-bremen.de/peid=cr-10.1007_s42058-019-00015-0&Exemplar=1&LAN=DE A1 Li, Qiong A1 Li, Qing-chu A1 Cao, Rui-ting A1 Wang, Xiang A1 Chen, Ru-tan A1 Liu, Kai A1 Fan, Li A1 Xiao, Yi A1 Zhang, Zi-tian A1 Fu, Chi-Cheng A1 Song, Qiong A1 Liu, Weiping A1 Fang, Qu A1 Liu, Shi-yuan PB Springer Science and Business Media LLC YR 2019 SN 2520-8985 SN 2520-8993 JF Chinese Journal of Academic Radiology VO 2 IS 1-2 SP 1 OP 12 LK http://dx.doi.org/https://doi.org/10.1007/s42058-019-00015-0 DO https://doi.org/10.1007/s42058-019-00015-0 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)