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
Facial Emotion Recognition Using Conventional Machine Learn..:
Amjad Rehman Khan
https://www.mdpi.com/2078-2489/13/6/268. , 2022
Link:
https://doi.org/10.3390/info13060268
RT Journal T1
Facial Emotion Recognition Using Conventional Machine Learning and Deep Learning Methods: Current Achievements, Analysis and Remaining Challenges
UL https://suche.suub.uni-bremen.de/peid=base-ftdoajarticles:oai:doaj.org_article:6785de3d4032454785b533ec2a4d4ebc&Exemplar=1&LAN=DE A1 Amjad Rehman Khan PB MDPI AG YR 2022 K1 facial expressions K1 facial emotion recognition (FER) K1 technological development K1 healthcare K1 security K1 deep learning and traditional classification methods K1 Information technology K1 T58.5-58.64 JF https://www.mdpi.com/2078-2489/13/6/268 LK http://dx.doi.org/https://doi.org/10.3390/info13060268 DO https://doi.org/10.3390/info13060268 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)