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
Analysing the power of deep learning techniques over the tr..:
Gurupur, Varadraj P.
;
Kulkarni, Shrirang A.
;
Liu, Xinliang
..
Journal of Experimental & Theoretical Artificial Intelligence. 31 (2018) 1 - p. 99-115 , 2018
Link:
https://doi.org/10.1080/0952813x.2018.1518999
RT Journal T1
Analysing the power of deep learning techniques over the traditional methods using medicare utilisation and provider data
UL https://suche.suub.uni-bremen.de/peid=cr-10.1080_0952813x.2018.1518999&Exemplar=1&LAN=DE A1 Gurupur, Varadraj P. A1 Kulkarni, Shrirang A. A1 Liu, Xinliang A1 Desai, Usha A1 Nasir, Ayan PB Informa UK Limited YR 2018 SN 0952-813X SN 1362-3079 JF Journal of Experimental & Theoretical Artificial Intelligence VO 31 IS 1 SP 99 OP 115 LK http://dx.doi.org/https://doi.org/10.1080/0952813x.2018.1518999 DO https://doi.org/10.1080/0952813x.2018.1518999 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)