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
Deep gramulator: Improving precision in the classification ..:
, In:
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
,
Calix, Ricardo A.
;
Gupta, Ravish
;
Gupta, Matrika
. - p. 1154-1159 , 2017
Link:
https://doi.org/10.1109/BIBM.2017.8217820
RT T1
2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
: T1
Deep gramulator: Improving precision in the classification of personal health-experience tweets with deep learning
UL https://suche.suub.uni-bremen.de/peid=ieee-8217820&Exemplar=1&LAN=DE A1 Calix, Ricardo A. A1 Gupta, Ravish A1 Gupta, Matrika A1 Jiang, Keyuan YR 2017 K1 Feature extraction K1 Drugs K1 Twitter K1 Surveillance K1 Neural networks K1 natural language processing K1 deep learning SP 1154 OP 1159 LK http://dx.doi.org/https://doi.org/10.1109/BIBM.2017.8217820 DO https://doi.org/10.1109/BIBM.2017.8217820 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)