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
3D-Based Facial Emotion Recognition using Depthwise Separab..:
, In:
2022 14th International Conference on Machine Learning and Computing (ICMLC)
,
Abubakar, Hassan Sani
;
Hossin, MD Altab
;
Yussif, Sophyani Banaamwini
... - p. 381-387 , 2022
Link:
https://dl.acm.org/doi/10.1145/3529836.3529855
RT T1
2022 14th International Conference on Machine Learning and Computing (ICMLC)
: T1
3D-Based Facial Emotion Recognition using Depthwise Separable Convolution
UL https://suche.suub.uni-bremen.de/peid=acm-3529855&Exemplar=1&LAN=DE A1 Abubakar, Hassan Sani A1 Hossin, MD Altab A1 Yussif, Sophyani Banaamwini A1 Fargalla, Mandela Ali Margan A1 Rashid, Ramadhan Said A1 Umar, Yusuf Jamilu A1 Chima, Ukwuoma Chiagoziem A1 Kuupole, Ewald Erubaar PB ACM YR 2022 K1 Convolutional neural network K1 Facial emotion recognition (FER) K1 Separable convolution K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks SP 381 OP 387 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3529836.3529855 DO https://dl.acm.org/doi/10.1145/3529836.3529855 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)