Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas

This project is to develop gender identification system prototype by using back propagation Neural Network (BPNN). Artificial Neural Network is widely used in classification problem and very usable for developing computer vision system. The system is expected to be able to identify and recognize the...

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Main Author:	Abas, Mohd Amin
Format:	Thesis
Language:	English
Published:	2006
Subjects:	Electronic Computers Computer Science
Online Access:	https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf
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id	my-uitm-ir.1593
record_format	uketd_dc
spelling	my-uitm-ir.15932023-08-11T02:48:33Z Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas 2006 Abas, Mohd Amin Electronic Computers. Computer Science This project is to develop gender identification system prototype by using back propagation Neural Network (BPNN). Artificial Neural Network is widely used in classification problem and very usable for developing computer vision system. The system is expected to be able to identify and recognize the genders of human. BPNN is a learning that learns by example (Negnevitsky, 2002). This project has been fully developed by Borland C-H- Builder 6 with assist by other software such as Adobe Photoshop as the im^e editor. The feature that has been used is human face itself with eyebrows has been extract as the information for the input node in the input layer. The performance of the network is 10% error based on 20-test subject. 2006 Thesis https://ir.uitm.edu.my/id/eprint/1593/ https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf text en public degree Universiti Teknologi MARA Faculty of Computer and Mathematical Sciences Ibrahim, Zaidah
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Ibrahim, Zaidah
topic	Electronic Computers Computer Science
spellingShingle	Electronic Computers Computer Science Abas, Mohd Amin Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
description	This project is to develop gender identification system prototype by using back propagation Neural Network (BPNN). Artificial Neural Network is widely used in classification problem and very usable for developing computer vision system. The system is expected to be able to identify and recognize the genders of human. BPNN is a learning that learns by example (Negnevitsky, 2002). This project has been fully developed by Borland C-H- Builder 6 with assist by other software such as Adobe Photoshop as the im^e editor. The feature that has been used is human face itself with eyebrows has been extract as the information for the input node in the input layer. The performance of the network is 10% error based on 20-test subject.
format	Thesis
qualification_level	Bachelor degree
author	Abas, Mohd Amin
author_facet	Abas, Mohd Amin
author_sort	Abas, Mohd Amin
title	Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title_short	Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title_full	Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title_fullStr	Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title_full_unstemmed	Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title_sort	development of human gender identification prototype using back-propagation neural network / mohd amin abas
granting_institution	Universiti Teknologi MARA
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2006
url	https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf
_version_	1783733035368185856

Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas

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