A Comparative Analysis of Feed-Forward and Generalized Regression Neural Networks for Face Recognition Using Principal Component Analysis
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2012, Vol 2, Issue 3
Abstract
In this paper we give a comparative analysis of performance of feed forward neural network and generalized regression neural network based face recognition. We use different inner epoch for different input pattern according to their difficulty of recognition. We run our system for different number of training patterns and test the system’s performance in terms of recognition rate and training time. We run our algorithm for face recognition application using Principal Component Analysis and both neural network. PCA is used for feature extraction and the neural network is used as a classifier to identify the faces. We use the ORL database for all the experiments.
Authors and Affiliations
Amit Kumar, Mr. Mahesh Singh
Keywords
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- EP ID EP649898
- DOI 10.24297/ijct.v2i3c.2714
- Views 119
- Downloads 0
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