Gender classification from face images using support vector machine

Investigated the performance of support vector machine on gender categorization using images. Radial Basic Kernel and two parameters of the RBF kernel were chosen. By using random selection of images for training the classifier in a series of runs, the accuracies were determined.

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Bibliographic Details
Main Author:	Phyu Phyu Thant.
Other Authors:	Sung, Eric
Format:	Theses and Dissertations
Published:	2008
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems
Online Access:	http://hdl.handle.net/10356/3139
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Institution:	Nanyang Technological University

id	sg-ntu-dr.10356-3139
record_format	dspace
spelling	sg-ntu-dr.10356-31392023-07-04T15:03:19Z Gender classification from face images using support vector machine Phyu Phyu Thant. Sung, Eric School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems Investigated the performance of support vector machine on gender categorization using images. Radial Basic Kernel and two parameters of the RBF kernel were chosen. By using random selection of images for training the classifier in a series of runs, the accuracies were determined. Master of Science (Computer Control and Automation) 2008-09-17T09:23:03Z 2008-09-17T09:23:03Z 2004 2004 Thesis http://hdl.handle.net/10356/3139 Nanyang Technological University application/pdf
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
topic	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems Phyu Phyu Thant. Gender classification from face images using support vector machine
description	Investigated the performance of support vector machine on gender categorization using images. Radial Basic Kernel and two parameters of the RBF kernel were chosen. By using random selection of images for training the classifier in a series of runs, the accuracies were determined.
author2	Sung, Eric
author_facet	Sung, Eric Phyu Phyu Thant.
format	Theses and Dissertations
author	Phyu Phyu Thant.
author_sort	Phyu Phyu Thant.
title	Gender classification from face images using support vector machine
title_short	Gender classification from face images using support vector machine
title_full	Gender classification from face images using support vector machine
title_fullStr	Gender classification from face images using support vector machine
title_full_unstemmed	Gender classification from face images using support vector machine
title_sort	gender classification from face images using support vector machine
publishDate	2008
url	http://hdl.handle.net/10356/3139
_version_	1772826825275211776

Gender classification from face images using support vector machine

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