| 000 | 02575nam a2200277 a 4500 | ||
|---|---|---|---|
| 001 | vtls000054751 | ||
| 003 | KUKTEM | ||
| 005 | 20251114204450.0 | ||
| 008 | 110714t2010 my a f m 000 0 eng d | ||
| 020 | _aTHE0007049(Local) | ||
| 039 | 9 |
_a201906131009 _bhanafiah _c201107141255 _dida _c201107141255 _dida _y201107141236 _zida |
|
| 040 | _aUMP | ||
| 090 | _aTK7882.B56 A44 2010 rs Bc. | ||
| 100 | 0 | _aAlfatihah Abdullah | |
| 245 | 1 | 0 |
_aFace recognition using neural network / _cAlfatihah Abdullah |
| 246 | 3 |
_aFace recognition using neural network _h[computer file] |
|
| 260 |
_aKuantan, Pahang : _bUMP, _c2010 |
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| 300 |
_axiv, 62 p. : _bill. (some col.) ; _c30 cm. + _e1 computer disc |
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| 502 | _aProject paper (Bachelor of Electrical Engineering (Electronics)) -- Universiti Malaysia Pahang - 2010 | ||
| 504 | _aBibliography : p. 57-59 | ||
| 520 | 3 | _aFacial recognition systems are computer-based security systems that are able to automatically detect and identify human faces. Facial recognition has gained increasing interest in the recent decade. Over the years there have been several techniques being developed to achieve high success rate of accuracy in the identification and verification of individuals for authentication in security systems. This project experiments the concept of neural network for facial recognition that can differentiate and recognize face of image. This face recognition system begins with image pre-processing and then the output image is trained using Backpropagation algorithm. Backpropagation network learns by training the inputs, calculating the error between the real output and target output, and propagates back the error to the network to modify the weights until the desired output is obtained. After training the network, the recognition system is tested to ensure that the system can recognize the pattern of each face image. The purpose of this project is to recognize face of image for the recognition analysis using Neural Network. This project is mainly concern with offline facial recognition systems using purely image processing technique. The system will find database image has a maximum percentage on similarity of the pattern of the image. This project is also to design a pattern recognition system by applying Neural Network Toolbox in MATLAB software. | |
| 650 | 0 | _aBiometric identification | |
| 650 | 0 | _aHuman face recognition (Computer science) | |
| 650 | 0 | _aNeural networks (Computer science) | |
| 999 |
_aVIRTUA40 _c2499 _d2505 |
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| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2460*2600*3000*5020*5040*5200*6500*6501*6502*9992 | ||