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
Density Dedicated Deep Learning Model for Mammogram Maligna..:
, In:
2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
,
Amini, Mehdi
;
Salimi, Yazdan
;
Mansouri, Zahra
... - p. 1-3 , 2022
Link:
https://doi.org/10.1109/NSS/MIC44845.2022.10398928
RT T1 <cTitle>2022 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)</cTitle>: T1 <Title>Density Dedicated Deep Learning Model for Mammogram Malignancy Classification</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-10398928&Exemplar=1&LAN=DE A1 Amini, Mehdi A1 Salimi, Yazdan A1 Mansouri, Zahra A1 Arabi, Hossein A1 Shiri, Isaac A1 Zaidi, Habib YR 2022 SN 2577-0829 K1 Deep learning K1 Training K1 Sensitivity K1 Training data K1 Breast K1 Mammography K1 Task analysis SP 1 OP 3 LK http://dx.doi.org/https://doi.org/10.1109/NSS/MIC44845.2022.10398928 DO https://doi.org/10.1109/NSS/MIC44845.2022.10398928 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
