Face recognition using soft computing methods
165 p.
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sg-ntu-dr.10356-391402023-07-04T17:34:16Z Face recognition using soft computing methods Chen, Weilong Er Meng Joo School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering 165 p. Human face recognition is still a challenging task for computer-based machines mainly due to the similarity of human faces and unpredictable variations such as illumination, pose, expression, occlusion etc. A lot of algorithms have been developed to deal with these challenging issues in face recognition. One of the difficult problems is the geometric variation of face images. In some face recognition applications, only face images with uncontrolled format are available. Face images obtained from face detection stage may be directly used. Therefore, alignment or normalization is required to achieve better recognition performance. Eye detection technique is normally used to normalize face images. Invariant representations are used to improve the generalization of facial features. Feature-based and modelbased automatic face alignment can also be used to localize human faces more precisely. DOCTOR OF PHILOSOPHY (EEE) 2010-05-21T04:45:30Z 2010-05-21T04:45:30Z 2006 2006 Thesis Chen, W. (2006). Face recognition using soft computing methods. Doctoral thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/39140 10.32657/10356/39140 application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Chen, Weilong Face recognition using soft computing methods |
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165 p. |
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Er Meng Joo |
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Er Meng Joo Chen, Weilong |
format |
Theses and Dissertations |
author |
Chen, Weilong |
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Chen, Weilong |
title |
Face recognition using soft computing methods |
title_short |
Face recognition using soft computing methods |
title_full |
Face recognition using soft computing methods |
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Face recognition using soft computing methods |
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Face recognition using soft computing methods |
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face recognition using soft computing methods |
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2010 |
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https://hdl.handle.net/10356/39140 |
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1772826690944237568 |