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KPCA与SVM共同用于人脸识别 SVM提高了分类效果 KPCA是一种借鉴SVM中核函数的一种较好的特征提取方法-KPCA and SVM for face recognition SVM together to improve the classification results from KPCA is a kernel function in SVM a better feature extraction method
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在ORL或Yale标准人脸数据库上完成模式识别任务。用PCA与基于核的PCA(KPCA)方法完成人脸图像的重构与识别试验.
-Or Yale in the ORL face database, complete the standard pattern recognition tasks. With the PCA and kernel-based PCA (KPCA) method to complete the reconstruction of face image and reco
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模式识别课程作业,pca和kpca,以及一个人脸可。其中kpca的核函数是多项式。-Pattern Recognition course assignments, pca and kpca, and a person can face. Where the kernel function is polynomial kpca.
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matlab 源码 KPCA/核PCA 可用于人脸识别-matlab source KPCA/nuclear PCA for Face Recognition
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非常有用的人脸识别工具包,包含了各种PCA,LDA, KPCA, KFA及其变种。在Matlab环境下可以直接运行。-The PhD (Pretty helpful Development functions for) face recognition toolbox is a collection of Matlab functions and scr ipts intended to help researchers working in the field of face recognit
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