基于神经网络集成和特征融合的人脸识别

2013 IEEE Third International Conference on Information Science and Technology (ICIST) Pub Date : 2013-03-23 DOI:10.1109/ICIST.2013.6747500

Jiwen Dong, Lei Zhao, Liang Zhang

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引用次数: 1

摘要

提出了一种基于集成神经网络的多特征融合方法。首先，利用KPCA算法提取整体识别特征;然后，利用KICA算法提取局部特征;最后，利用BP和PNN神经网络对两种算法的结果进行识别。该方法解决了外界因素的干扰，分类正确率高。

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Face recognition based on neural network ensemble and feature fusion

In this paper, a fusion of multiple features method based on integrated neural network was proposed. Firstly, KPCA algorithm was used to extract the overall recognition features. Then, the KICA algorithm was used to extract the local features. Finally, the BP and PNN neural network were used to recognize the result of the both algorithms. The method solved the interference caused by the external factors and got high correct rate of classification.

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2013 IEEE Third International Conference on Information Science and Technology (ICIST)

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