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svm
- 支持向量机(SVM)、线形鉴别分析(LDA)、主分量分析(PCA)和人工神经元网络(ANN)源代码
模式识别matlab工具箱,包括svm,ICA,PCA,NN等等模式识别算法
- 模式识别matlab工具箱,包括svm,ICA,PCA,NN等等模式识别算法
matlab-PCA 基于matlab的PCA人脸识别完成程序
- 基于matlab的PCA人脸识别完成程序，包含特征值与特征向量的提取、训练样本以复制到matlab即可，成功运行，及最后的识别检验-A full implementation of ICA,PCA,LDA,SVM,in both orginal and incremental in model of real time learnign for face recognition
PCA_SVM.rar
- 此方法采用经典的PCA对人脸图像进行特征提取，用libsvm库函数的SVM分类器对图像分类。,This method uses the classical PCA on the face image feature extraction, with the libsvm library function of SVM classifier for image classification.
PCA-SVM-face-recognition
- 用PCA 和 SVM 做的人脸识别程序，与大家分享！-To do with PCA and SVM face recognition program, to share with you!
FaceRec
- 基于matlab2008的人脸识别系统，使用了PCA +Adaboost与PCA+SVM分别实现了人脸识别，使用了orl人脸库，给一个人的图片就可以识别此人身份，识别率高达84 -Matlab2008 face recognition system based on use of the PCA + Adaboost achieved with the PCA+ SVM face recognition, respectively, using the orl face database
kpca
- 使用核PcA来识别图片，图片为200张测试图片，200张训练图片，包含在在压缩文件中。-To identify the use of nuclear PcA picture, pictures, for 200 test images, 200 training images, is included in the compressed file.
face-recognition
- 含有PCA经典人脸识别方法和PCA+SVM人脸识别方法-Classical Face Recognition with PCA and PCA+ SVM face recognition method
PCA-(ICA)
- 主成分分析程序包，包括主成分分析和独立主成分分析两个程序源代码。-Principal component analysis package, including principal component analysis principal component analysis and independent source code for both procedures.
pca-svm
- pca的matlab实现,very good-achievement of pca with matlab
pcakenelfunction
- pca分解的核函数，在pca分解中可以用到，特别是分解的矩阵维数比较高的情况下，通过svd分解获得pca基-pca decomposition of the kernel function, in the pca decomposition can be used, in particular the decomposition of the matrix of higher dimension, through the svd decomposition was pca-based
pca_knn
- 本方法采用pca进行特征提取，knn分类器进行人脸识别。-The method of feature extraction using pca, knn classifier for face recognition.
chapter13
- 《数字图像处理与机器视觉:Visual C++与Matlab实现》6 支持向量机,综合案例——基于PCA和SVM的人脸识别系统-" Digital image processing and machine vision: Visual C++ and Matlab to achieve" 6 support vector machines, comprehensive case- based on PCA and SVM for Face Recognition Syste
PCA-SVM
- 人脸识别程序 程序源代码可见 识别精度高PCA-SVM-Face Recognition program PCA-SVM
pca-svm
- 基于pca的人脸识别程序，人脸库需要自己下载，供参考-Pca-based face recognition program needs to download face database, for reference
gabor-pca
- 本程序是先用gabor小波变换对人脸图像处理，然后在用pca进行降维，最后用svm分类器进行多分类分类识别，包扩完整的orl人脸库，需注意的是，svm工具箱是用的libsvm工具箱，运行前先配置好libsvm。版本号：libsvm-mat-2[1].89-3[FarutoUltimate3.0]-This procedure is to use the human face gabor wavelet transform image processing, and then to reduce
PCA-and-SVM-Face-recognition
- 采用PCA对人脸特征进行抽取，用SVM多累分类器对人脸进行识别，有操作界面-Using PCA for facial feature extraction, and more tired with the SVM classifier for face identification, a user interface
face-gabor-pca
- 基于gabor的人脸识别 带有pca降维 最后用svm识别-Finally, svm pca dimensionality reduction recognition with face recognition based on gabor
python_face_recog
- 基于python+opencv 的 人脸识别，对一段视频进行读取，并检测出人脸，然后进行PCA 降维，最后用SVM进行人脸识别，识别率94%左右。(Based on python + opencv face recognition, a video was read, and face detection, and then PCA dimension reduction, and finally SVM face recognition, recognition rate of about 9
PCA+SVM
- 先用PCA降维，在利用支持向量机进行分类，这个分类是二分类，所以PCA的降维降到两维即可分类。(Firstly, PCA dimensionality reduction is used to conduct classification with support vector machine. This classification is binary classification, so the dimensionality reduction of PCA can be reduced t