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

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題名:	2D/3D Face Recognition Using Neural Network Based on Hybrid Taguchi-Particle Swarm Optimization
作者:	林正堅
貢獻者:	資訊工程系
日期:	2011-02
上傳時間:	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)
顯示於類別:	[資訊工程系(所)] 【資訊工程系所】期刊論文

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