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
CNN-LSTM To Identify The Most Informative EEG-Based Driver ..:
, In:
2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
,
Latreche, Imene
;
Slatnia, Sihem
;
Kazar, Okba
- p. 725-730 , 2022
Link:
https://doi.org/10.1109/ISMSIT56059.2022.9932696
RT T1
2022 International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
: T1
CNN-LSTM To Identify The Most Informative EEG-Based Driver Drowsiness Detection Brain Region
UL https://suche.suub.uni-bremen.de/peid=ieee-9932696&Exemplar=1&LAN=DE A1 Latreche, Imene A1 Slatnia, Sihem A1 Kazar, Okba YR 2022 SN 2770-7962 K1 Electrodes K1 Deep learning K1 Costs K1 Wearable computers K1 Scalp K1 Signal processing K1 Brain modeling K1 Driver Drowsiness K1 Electroencephalogram (EEG) K1 Deep Learning K1 Brain regions K1 CNN K1 LSTM SP 725 OP 730 LK http://dx.doi.org/https://doi.org/10.1109/ISMSIT56059.2022.9932696 DO https://doi.org/10.1109/ISMSIT56059.2022.9932696 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)