2D/3D Face Recognition Using Neural Network Based on Hybrid Taguchi-Particle Swarm Optimization

勤益科大機構典藏 > 電資學院 > 資訊工程系(所) > 【資訊工程系所】期刊論文 > Item 987654321/6872

jsp.display-item.identifier=請使用永久網址來引用或連結此文件: http://ir.lib.ncut.edu.tw/handle/987654321/6872

题名:	2D/3D Face Recognition Using Neural Network Based on Hybrid Taguchi-Particle Swarm Optimization
作者:	林正堅
贡献者:	資訊工程系
日期:	2011-02
上传时间:	2017-12-17 13:09:55 (UTC+8)
摘要:	In this paper, we present a neural network classifier with hybrid evolutionary algorithm for solving 2D/3D face recognition problems. We first use Gabor wavelets to extract local features at different scales and orientations for gray facial images, then combine the texture with the surface feature vectors based on principal component analysis (PGA) to obtain feature vectors. We propose a neural network classifier based on hybrid Taguchi-particle swarm optimization (HTPSO) algorithm for face recognition. Experimental results demonstrate that the proposed HTPSO learning method has a better recognition rate than those of other approaches. ICIC International © 2011. (28 refs)
關聯:	International Journal of Innovative Computing, Information and Control (IJICIC)
显示于类别:	[資訊工程系(所)] 【資訊工程系所】期刊論文

文件中的档案:

没有与此文件相关的档案.

检视Licence

在NCUTIR中所有的数据项都受到原著作权保护.