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
MD-CardioNet: A Multi-Dimensional Deep Neural Network for C..:
Tahmid, Md Toki
;
Kader, Muhammad Ehsanul
;
Mahmud, Tanvir
.
IEEE Journal of Biomedical and Health Informatics. 28 (2024) 4 - p. 2005-2013 , 2024
Link:
https://doi.org/10.1109/jbhi.2023.3308856
RT Journal T1 <Title>MD-CardioNet: A Multi-Dimensional Deep Neural Network for Cardiovascular Disease Diagnosis From Electrocardiogram</Title> UL https://suche.suub.uni-bremen.de/peid=cr-10.1109_jbhi.2023.3308856&Exemplar=1&LAN=DE A1 Tahmid, Md Toki A1 Kader, Muhammad Ehsanul A1 Mahmud, Tanvir A1 Fattah, Shaikh Anowarul PB Institute of Electrical and Electronics Engineers (IEEE) YR 2024 SN 2168-2194 SN 2168-2208 JF IEEE Journal of Biomedical and Health Informatics VO 28 IS 4 SP 2005 OP 2013 LK http://dx.doi.org/https://doi.org/10.1109/jbhi.2023.3308856 DO https://doi.org/10.1109/jbhi.2023.3308856 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
