Facial expression recognition based on conjugate gradient extreme learning machine

Jian Chen
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引用次数: 1

Abstract

This paper proposed a face recognition algorithm based on conjugate gradient extreme learning machine. General extreme learning machine algorithm, which is gained by using method of calculating generalized inverse, the process is a large amount of computation and memory consumption. For this problem, this paper proves the positive definiteness of the calculated matrix, and based on this, an extreme learning machine solution algorithm based on conjugate gradient algorithm was proposed and kernel function is introduced to improve its nonlinear classification performance. At the same time, DAG method is used to extend the binary classification conjugate gradient extreme learning machine to multi-classification problems. Experimental results show that the computational speed of the algorithm in this paper is faster than that of the general extreme learning machine algorithm, and the classification accuracy is higher than that of the general extreme learning machine algorithm.
基于共轭梯度极值学习机的面部表情识别
提出了一种基于共轭梯度极值学习机的人脸识别算法。一般极值学习机算法,它是通过计算广义逆的方法得到的,该过程计算量大,内存消耗大。针对这一问题,本文证明了计算矩阵的正定性,并在此基础上提出了一种基于共轭梯度算法的极限学习机求解算法,并引入核函数来提高其非线性分类性能。同时,利用DAG方法将二分类共轭梯度极值学习机扩展到多分类问题。实验结果表明,本文算法的计算速度比一般极限学习机算法快,分类准确率也高于一般极限学习机算法。
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