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核直接线性判别方法:图像及高维复杂数据模式识别的利器!内有方法开发的相关文档说明!经典!-The matlab functions implement the methods presented in the paper [TNN_KDDA02.pdf]
Juwei Lu, K.N. Plataniotis, and A.N. Venetsanopoulos, "Face Recognition Using
Kernel Direct Discriminant Anal
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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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Paper on non linear discriminant analysis.
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This my course final project for biometrics. It implements a robust face recognition system. Techniques used include Log-Gabor filter , Kernel Discriminant Analysis(KDA) and Sparse Representation . Test data included(ORL database of faces).-This is m
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基于PCA的人脸识别 Matlab代码 两种方法 KL 和kernel-PCA-based face recognition Matlab code
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核主成分分析,用于轴承故障,人面识别,水位分布等的数据非线性提取。-Kernel principal component analysis for data bearing failure, human face recognition, water distribution and other non-linear extraction.
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经典kernel LDA算法,可用于人脸识别算法,很好用(Classic kernel LDA algorithm, can be used for face recognition algorithm, very good use)
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