1) complete Two-dimensional Principle Component Analysis(2DPCA)
完全二维主元分析
2) Complete Two Dimensional Principal Component Analysis (C2DPCA)
完全二维主成分分析(C2DPCA)
3) Subpattern Complete Two Dimensional Principal Component Analysis (SpC2DPCA)
子模式的完全二维主成分分析(SpC2DPCA)
4) WC2DPCA(weighted complete two-dimensional principal component analysis)
加权完全的二维主成分分析
5) Two-dimensional Principal Component Analysis(2DPCA)
二维主元分析
1.
In combination with Wavelet Transform(WT),Two-dimensional Principal Component Analysis(2DPCA) and Ellipsoidal Basis Function(EBF),a fingerprint recognition algorithm based on WT,2DPCA and EBF neural network(EBFNN) is proposed.
结合小波变换(WT)、二维主元分析(2DPCA)和椭球基函数(EBF)特点,提出了一种基于WT、2DPCA和EBF神经网络指纹识别方法。
2.
Combined with Discrete Cosine Transform(DCT) and Two-Dimensional Principal Component Analysis(2DPCA),a novel method in face recognition was presented in this paper.
提出了一种对角离散余弦变换(Discrete Cosine Transform,DCT)和二维主元分析(Two-Dimensional Principal Component Analysis,2DPCA)相结合的人脸识别方法。
3.
Combined with the characteristics of two-dimensional principal component analysis(2DPCA),2DPCA algorithm is applied in face recognition.
结合二维主元分析(two-dimensionalprincipalcomponentanalysis,2DPCA)的特点,将2DPCA算法用于人脸识别。
6) 2DPCA
二维主元分析
1.
Two-dimensional Principle Component Analysis (2DPCA) is used to compute covariance matrix directly according to two-dimensional matrix of face image, which is not be transformed into vector, and computation of eigenvalues and eigen.
二维主元分析(Two-dimensional Principle Component Analysis,2DPCA)无须将人脸图像矩阵转换成向量,直接利用二维人脸图像矩阵求协方差矩阵,其特征值与特征向量的计算得到简化。
2.
Some of face recognition methods based on Principal Component Analysis(PCA),Two-dimensional Principal Component Analysis(2DPCA) and Fisher s Linear Discriminant Analysis(FLDA) are comparatively studied in this paper.
对基于主元分析(PCA)、二维主元分析(2DPCA)和Fisher线性判别分析(FLDA)的人脸识别方法进行了比较研究。
补充资料：上川主武元衡相国二首
【诗文】：
落日重城夕雾收，玳筵雕俎荐诸侯。
因令朗月当庭燎，不使珠帘下玉钩。
东阁移尊绮席陈，貂簪龙节更宜春。
军城画角三声歇，云幕初垂红烛新。
【注释】：
【出处】：
全唐诗
落日重城夕雾收，玳筵雕俎荐诸侯。
因令朗月当庭燎，不使珠帘下玉钩。
东阁移尊绮席陈，貂簪龙节更宜春。
军城画角三声歇，云幕初垂红烛新。
【注释】：
【出处】：
全唐诗
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条