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
Automatic assessment of Parkinson's patients' dyskinesia us..:
, In:
2022 International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET)
,
Theofilou, Paraskevi Antonia
;
Tsatiris, Georgios
;
Kollias, Stefanos
- p. 1-4 , 2022
Link:
https://doi.org/10.1109/IMET54801.2022.9929825
RT T1 <cTitle>2022 International Conference on Interactive Media, Smart Systems and Emerging Technologies (IMET)</cTitle>: T1 <Title>Automatic assessment of Parkinson's patients' dyskinesia using non-invasive machine learning methods</Title> UL https://suche.suub.uni-bremen.de/peid=ieee-9929825&Exemplar=1&LAN=DE A1 Theofilou, Paraskevi Antonia A1 Tsatiris, Georgios A1 Kollias, Stefanos YR 2022 K1 Measurement K1 Parkinson's disease K1 Machine learning K1 Media K1 Convolutional neural networks K1 Parkinson's Disease K1 Unified Dyskinesia Rating Scale (UDysRS) K1 Machine Learning K1 Convolutional Neural Networks K1 Action Recognition SP 1 OP 4 LK http://dx.doi.org/https://doi.org/10.1109/IMET54801.2022.9929825 DO https://doi.org/10.1109/IMET54801.2022.9929825 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)
