Facial Expression Classification In E-Learning Systems

The main objective of this research is to study the feasibility of classifying e-learning facial expressions by using current available techniques, Back-propagation Neural network (BPNN) and Support Vector Machine(SVM).

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Bibliographic Details
Main Author:	Loh, May Ping
Format:	Thesis
Published:	2007
Subjects:	LC Special aspects of education
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id	my-mmu-ep.1222
record_format	uketd_dc
spelling	my-mmu-ep.12222010-08-19T08:08:30Z Facial Expression Classification In E-Learning Systems 2007-03 Loh, May Ping LC Special aspects of education The main objective of this research is to study the feasibility of classifying e-learning facial expressions by using current available techniques, Back-propagation Neural network (BPNN) and Support Vector Machine(SVM). 2007-03 Thesis http://shdl.mmu.edu.my/1222/ http://myto.perpun.net.my/metoalogin/logina.php masters Multimedia University Research Library
institution	Multimedia University
collection	MMU Institutional Repository
topic	LC Special aspects of education
spellingShingle	LC Special aspects of education Loh, May Ping Facial Expression Classification In E-Learning Systems
description	The main objective of this research is to study the feasibility of classifying e-learning facial expressions by using current available techniques, Back-propagation Neural network (BPNN) and Support Vector Machine(SVM).
format	Thesis
qualification_level	Master's degree
author	Loh, May Ping
author_facet	Loh, May Ping
author_sort	Loh, May Ping
title	Facial Expression Classification In E-Learning Systems
title_short	Facial Expression Classification In E-Learning Systems
title_full	Facial Expression Classification In E-Learning Systems
title_fullStr	Facial Expression Classification In E-Learning Systems
title_full_unstemmed	Facial Expression Classification In E-Learning Systems
title_sort	facial expression classification in e-learning systems
granting_institution	Multimedia University
granting_department	Research Library
publishDate	2007
_version_	1747829320255012864

Facial Expression Classification In E-Learning Systems

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