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
Learning Deep Spatiotemporal Feature for Engagement Recogni..:
, In:
2019 IEEE Symposium Series on Computational Intelligence (SSCI)
,
Geng, Lin
;
Xu, Min
;
Wei, Zeqiang
. - p. 442-447 , 2019
Link:
https://doi.org/10.1109/SSCI44817.2019.9002713
RT T1
2019 IEEE Symposium Series on Computational Intelligence (SSCI)
: T1
Learning Deep Spatiotemporal Feature for Engagement Recognition of Online Courses
UL https://suche.suub.uni-bremen.de/peid=ieee-9002713&Exemplar=1&LAN=DE A1 Geng, Lin A1 Xu, Min A1 Wei, Zeqiang A1 Zhou, Xiuzhuang YR 2019 K1 Feature extraction K1 Videos K1 Convolution K1 Spatiotemporal phenomena K1 Three-dimensional displays K1 Data mining K1 Kernel K1 engagement recognition K1 spatiotemporal features K1 Convolutional 3D K1 class-imbalanced K1 Focal Loss SP 442 OP 447 LK http://dx.doi.org/https://doi.org/10.1109/SSCI44817.2019.9002713 DO https://doi.org/10.1109/SSCI44817.2019.9002713 SF ELIB - SuUB Bremen
Export
RefWorks (nur Desktop-Version!)
Flow
(Zuerst in
Flow
einloggen, dann importieren)