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用主成分分析法提取人脸图像特征的程序,算法理论依据是K-L变换,Principal Component Analysis with face image feature extraction process
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PCA,主成分分析,可应用于矩阵降维,人脸特征提取及人脸识别。-PCA, principal component analysis, can be applied to matrix reduction, facial feature extraction and face recognition.
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此程序用来对单波段图像或者多波段图像进行主成分分析,可以对主成分个数进行手动设置-This procedure used for single-band image or multi-band images, principal component analysis, the number of principal components can be manually set
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高维PCA
参考文献:
MPCA Multilinear Principal Component Analysis of Tensor Objects-High-dimensional PCA References: MPCA Multilinear Principal Component Analysis of Tensor Objects
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主分量分析,用于高维数据降维或提取目标特征。程序精简,效率高.
-Principal Component Analysis is used to make data dimensionality reduction or extract target characteristics。
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基于主成份分析(PCA)的人脸识别算法MATLAB程序的实现。机器视觉的作业,内附人脸识别的matlab程序,和人脸库,还有作业的详细要求,以及格式示例和部分参考文献。-Based on principal component analysis (PCA) of the face recognition algorithm MATLAB program implementation. Machine vision operations, included face recognition mat
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主成分分析,可以用来做人脸识别的程序,方便,快捷-Principal component analysis, face recognition can be used to do the procedure, convenient and fast
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主成分分析ppt。对做图像分析以及融合很有帮助。从别处转来的。希望有用。-Principal component analysis ppt. Right to do image analysis and fusion helpful. Have been transferred there. Want to be useful.
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PCA主成分分析,用于人脸识别,特征提取等-PCA principal component analysis for face recognition, feature extraction, etc.
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主元分析 (Principal Component Analysis, PCA) 又叫:Karhunen-Loeve变换
(KLT)、Hotelling变换。
假设已经从图象已经缩放为N*M大小。
m幅N*M大小的图象Xi作为n*1列向量看待-PCA (Principal Component Analysis, PCA) also known as: Karhunen-Loeve Transform (KLT), Hotelling transform.
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主分量分析(PCA ) 是统计学中分析数据的一种有效的方法, 可以将数据从高维数据空间变换到低维特征空间, 因而
可以用于数据的特征提取及压缩等方面。在该文的形状识别系统中, 用PCA 法提取图像的形状特征, 能够较好地满足识别
层的输入要求。在识别层研究了3 种识别方法: 最近邻法则、BP 网络及协同神经网络方法, 均取得了满意的实验效果。-Principal component analysis (PCA) is a statistical analysis of data in a
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PCA代码
主成分分析代码
适合初学人脸识别的朋友学习使用-PCA principal component analysis source code suitable for beginner learning to use face recognition friend
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这是一个主成分分析的matlab程序,非常有用。-This is a principal component analysis of matlab procedures, very useful.
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关于主成份分析的vc++源码,注释详细,以KL变换为基础,使特征将维。-Principal component analysis on the vc++ Source, comments, detail, based on KL transform, so that will be characterized by Victoria.
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matlab PCA,主成分分析经典算法-matlab PCA, principal component analysis of the classic algorithm
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为解决PCA不适合多指标综合分析中非线性主成分分析的问题 ,采用核主成分分析 (kpca)方法 ,对我国不同地区 16种腐乳的品质进行了综合评价。
-PCA is not suitable to address the many indicators of a comprehensive analysis of non-linear principal component analysis of the problem, using Kernel Principal Component An
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PCA 主成分分析在人脸识别中的应用 基于主成分分析理论对不同人脸库进行学习 总结“经验”并将“经验”用于对人脸的识别中-PCA Principal Component Analysis for Face Recognition Based on principal component analysis theory of different learning face database summary of " experience" and " experience
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主成分分析,人脸识别,模式识别,对图像处理有点帮助-Principal component analysis, face recognition, pattern recognition, image processing for a little help
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This programme is to calculate the principal component analysis (PCA) of a image. Naturally it is used to reduce the dmentionality of the image.
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基于主成分分析的人脸识别,本程序给出了N次重复实验后各维数的识别率-Principal Component Analysis(PCA)for face recognition
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