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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Bibliographic Details
Main Author: Abas, Mohd Amin
Format: Thesis
Language:English
Published: 2006
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf
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author Abas, Mohd Amin
author_facet Abas, Mohd Amin
author_sort Abas, Mohd Amin
collection UITM
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.
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spelling oai:ir.uitm.edu.my:15932023-08-11T02:48:33Z https://ir.uitm.edu.my/id/eprint/1593/ Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas 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 NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas. (2006) Degree thesis, thesis, Universiti Teknologi MARA.
spellingShingle Electronic Computers. Computer Science
Abas, Mohd Amin
Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas
title 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_short 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
topic Electronic Computers. Computer Science
url https://ir.uitm.edu.my/id/eprint/1593/2/1593.pdf
work_keys_str_mv AT abasmohdamin developmentofhumangenderidentificationprototypeusingbackpropagationneuralnetworkmohdaminabas