Real-time human expression recognition using deep learning on embedded system

Technology ease human life in every aspects. Some machine save human’s effort, some machine save time and increase efficiency in work. Machine is designed to complete specific task or multiple tasks without any intelligence needed. The next level of machine is machine which has intelligent and capab...

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Bibliographic Details
Main Author:	Goh, Yen Chang
Format:	Thesis
Language:	English
Published:	2018
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/id/eprint/79302/1/GohYenChangMFKE2018.pdf
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id	my-utm-ep.79302
record_format	uketd_dc
spelling	my-utm-ep.793022018-10-14T08:42:09Z Real-time human expression recognition using deep learning on embedded system 2018 Goh, Yen Chang TK Electrical engineering. Electronics Nuclear engineering Technology ease human life in every aspects. Some machine save human’s effort, some machine save time and increase efficiency in work. Machine is designed to complete specific task or multiple tasks without any intelligence needed. The next level of machine is machine which has intelligent and capable to think like human being while doing jobs, moreover, learn by themselves. Recently, Machine Learning are becoming more and more popular in 21stcentury. Machine learning can explores study and algorithms construction for making prediction. Data analytic by machine learning is a trend that used by Google, Facebook, Baidu and others big company nowadays. One of data analysis in machine learning which is Human Facial Expression Recognition is one of the hot topics now. Many researchers are proposed their techniques used in emotion recognition like PCA, LBP and etc. Goal in this project, is to analyze Inception v-3, the best performing high resolution image classifier based on Convolutional Neural Network, and also implement it in Raspberry Pi to see how it performs on detecting Facial Expressions. 2018 Thesis http://eprints.utm.my/id/eprint/79302/ http://eprints.utm.my/id/eprint/79302/1/GohYenChangMFKE2018.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Electrical Engineering Faculty of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Goh, Yen Chang Real-time human expression recognition using deep learning on embedded system
description	Technology ease human life in every aspects. Some machine save human’s effort, some machine save time and increase efficiency in work. Machine is designed to complete specific task or multiple tasks without any intelligence needed. The next level of machine is machine which has intelligent and capable to think like human being while doing jobs, moreover, learn by themselves. Recently, Machine Learning are becoming more and more popular in 21stcentury. Machine learning can explores study and algorithms construction for making prediction. Data analytic by machine learning is a trend that used by Google, Facebook, Baidu and others big company nowadays. One of data analysis in machine learning which is Human Facial Expression Recognition is one of the hot topics now. Many researchers are proposed their techniques used in emotion recognition like PCA, LBP and etc. Goal in this project, is to analyze Inception v-3, the best performing high resolution image classifier based on Convolutional Neural Network, and also implement it in Raspberry Pi to see how it performs on detecting Facial Expressions.
format	Thesis
qualification_level	Master's degree
author	Goh, Yen Chang
author_facet	Goh, Yen Chang
author_sort	Goh, Yen Chang
title	Real-time human expression recognition using deep learning on embedded system
title_short	Real-time human expression recognition using deep learning on embedded system
title_full	Real-time human expression recognition using deep learning on embedded system
title_fullStr	Real-time human expression recognition using deep learning on embedded system
title_full_unstemmed	Real-time human expression recognition using deep learning on embedded system
title_sort	real-time human expression recognition using deep learning on embedded system
granting_institution	Universiti Teknologi Malaysia, Faculty of Electrical Engineering
granting_department	Faculty of Electrical Engineering
publishDate	2018
url	http://eprints.utm.my/id/eprint/79302/1/GohYenChangMFKE2018.pdf
_version_	1747818195267354624

Real-time human expression recognition using deep learning on embedded system

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