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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Format: | Thesis |
Language: | English |
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2006
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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. |
first_indexed | 2024-03-06T01:19:51Z |
format | Thesis |
id | oai:ir.uitm.edu.my:1593 |
institution | Universiti Teknologi MARA |
language | English |
last_indexed | 2024-03-06T01:19:51Z |
publishDate | 2006 |
record_format | dspace |
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 |