搜索资源列表
PCA
- 快速PCA,对样本矩阵进行快速主成分分析,和降维,输出特征向量矩阵。-Rapid PCA, the sample matrix of fast principal component analysis , dimensional reduction
PCA
- 用matlab实现的PCA算法,用于人脸检测和识别,人脸图像的特征提取-algorithm of PCA of face detection by matlab
PCA
- C语言源程序,PCA人脸识别算法,主要是eig特征分量选取的源程序和欧式空间匹配程序、特征脸提取程序-C language source code, PCA face recognition algorithm, eig characteristic component selected source and match the European space program, eigenface extraction procedures
PCA
- PCA(主成分分析法)和ICA(独立成分分析法)的MATLAB源程序,他们是目前图像处理比较经典的特征提取方法-PCA (Principal Component Analysis) -matlab function of pca and ica of the signal
MATLAB-pca
- 这是主成分分析的matlab源程序,用于故障诊断的特征提前,请大家使用-This is original program of matlab,and it can be used for fault diagnosis.Welcome to used it.
PCA-based-face-recognition
- 研究内容包括四个方面:分别是人脸检测,图像的预处理,特征提取和人脸识别。能在不同光照,不同表情,不同姿态的情况下获得准确的识别。-The study includes four aspects: face detection, image preprocessing, feature extraction and face recognition. The accurate identification can be obtained in the case of different light
PCA-SIFT
- PCA——SIFT 特征值提取算法实现 用于图形图像处理的sift特征提取-PCA- SIFT the eigenvalue extraction algorithms to achieve
shouxieshuzi
- 里面包含了手写数字识别代码,有PCA特征提取,FSVM分类器识别,是很好的学习资源-Which contains a handwritten digital identification code, PCA feature extraction, FSVM classifiers recognition, is a good learning resource
pca
- 主成分分析法实现了对于多维特征的优化,共两个文件,希望对大家有帮助-failed to translate
PCA-SIFT
- 特征提取代码,提取pca_sift特征,用于图像特征提取,图像配准或匹配,可供做这方面研究的同学参考。-feature extraction image matching
PCA
- 提出了一种二维类增广PCA(2DCAPCA)的人脸识别算法。用二维PCA(2DPCA)方法直接对人脸图像矩阵进行特征提取,对提取的特征进行归一化处理,将归一化处理后的特征与类别信息结合构成类增广矩阵,对类增广矩阵进行2DPCA处理,提 取图像的类增广矩阵特征-This paper proposes a face recognition approach of two-dimension class-augmented PCA.
PCA
- pca人脸识别 基于代数统计的方法是使用统计学观点提取基向量,之后将人脸向量投影到基向量上,得到的投影值即为不同的人脸图像特征,这种方法利于操作,比较灵活。本次设计采用PCA方法对人脸进行降维,提取特征。 -pca face recognition based on the statistical method Generation is extracted base vectors using a statistical point of view, and then the vector
PCA
- 基于PCA的人脸识别,识别率的输出,人脸特征的提取。-PCA-based face recognition, the recognition rate of output, face feature extraction.
mel-pca
- MFCC特征提取实例 MFCC特征提取实例 -Examples MFCC feature extraction
pca
- 主成分分析算法程序 选取前多少个主成分代表主要特征-Principal component analysis algorithm select the top number represents the main features of the main components
pca
- pca算法实现人脸识别,包括数据图片,特征提取算法,最近邻分类器算法-pca algorithm for face recognition, including data pictures, feature extraction algorithm, nearest neighbor classifier algorithms, etc.
pca
- pca算法已经广泛应用于各方面,当提取的图像特征维度比较高时,为了简化计算量以及储存空间,需要对这些高维数据进行一定程度上的降维,并尽量保证数据的不失真。-pca algorithm has been widely used in various areas, when the extracted image feature dimension is relatively high, in order to simplify the calculation and storage space n
PCA-code
- 文档包括:CreatDatabase.m ,特征脸和识别三个m文件,有一定的用处。-Documentation includes: CreatDatabase.m, characteristic face and identify three m file, have a certain usefulness.
pca
- 集成了C代码和MATLAB的主成分分析代码,可以用这两种方法解决求取特征值和特征向量。-C code and MATLAB integrates principal component analysis code, you can use two methods to solve strike eigenvalues and eigenvectors.
PCA
- 主成分分析的matlab编码,用于矩阵求特征值特征向量-Principal component analysis matlab coding for matrix eigenvalue eigenvector