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

Abas, Mohd Amin (2006) Development of human gender identification prototype using back-propagation neural network / Mohd Amin Abas. Degree thesis, Universiti Teknologi MARA.

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Abstract

This project is to develop gender identification system prototype by using backpropagation
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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Item Type: Thesis (Degree)
Creators:
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Abas, Mohd Amin
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Subjects: Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences
Item ID: 1593
URI: https://ir.uitm.edu.my/id/eprint/1593

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