搜索资源列表
haykin_nn
- Simon Haykin的 《Neural NetWorks》例子原码，相当经典。相信很有用，特别SVM PCA等-Simon Haykin "Neural NetWorks" examples of the original code, very classic. I believe very useful, especially in such SVM PCA
Classification-MatLab-Toolbox
- 模式识别matlab工具箱,包括SVM,ICA,PCA,NN等等模式识别算法,很有参考价值-pattern recognition Matlab toolbox, including SVM, ICA, PCA, NN pattern recognition algorithms, and so on, of great reference value
biaoqing
- 一个表情识别的源码。直接调用pca和svm函数。-an expression recognition of the source. Pca and direct calling svm function.
Yale_PCASVM
- 在Yale 人脸库上运用PCA＋SVM的方法实现了人脸检测，并统计识别率
facedetect_byxzq
- 一个外国人写的人脸检测程序，用到svm,pca,神经网络,还不错
facedetector
- 人脸检测源代码. The souce demonstrates face detection SSE optimized C++ library for color and gray scale data with skin detection, motion estimation for faster processing, small sized SVM and NN rough face prefiltering, PCA/LDA/ICA/any dimensionality reduct
边缘检测算法
- 该工具箱专为模式识别定制，主要是数字图像识别，比如特征提取、图像分类、PCA、LDA、ICA、DCT、RBF、RBE、GRNN、KNN、minimum distance、SVM等等
DIPDemo
- 《数字图像处理与机器视觉:Visual C++与Matlab实现》7 V图像的点运算,几何变换, 图像增强,彩色图像处理,实用案例——汽车牌照的投影失真校正-" 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 Re
PCA_ORL
- Matlab环境下，实现用PCA方法提取EigenFace,之后通过SVM方法对人脸图像进行分类识别。-Face recognition via PCA and SVM method
FaceRec
- 人脸识别（PCA+SVM） 文件中包含训练样本，运行后，能进行人脸识别，采用PCA进行降维，利用ＳＶＭ 进行分类识别-Face recognition（PCA+SVM）
Attribute profiles
- 选择合适的样本特征点，然后可以将特征导入svm进行分类(After the image processing, the main information is obtained by PCA transform, and then the feature of texture information selection is put forward)
SVM-KMExample
- examples of SVM, PCA , MultiSVM, Feature extraction, kernel function
基于主分量的人脸重构
- 本实验是基于主成分分析法（PCA）在人脸识别中的应用，采用SVM分类器在ORL人脸库的基础上通过Matlab实现了快速PCA算法的验证仿真。
(PCA+SVM)人脸识别
- 人脸识别，降维 加分类，主成分分析降维，支持向量机分类(Face recognition, principal component analysis reduced Vega classification, dimension reduction, support vector machine classification)
face-Adaboost
- 用Adaboost和PCA算法实现人脸识别，用Python写的代码，根据经典的PCA和SVM算法改编(Adaboost and PCA algorithm for face recognition, code written in Python, adapted from the classic PCA and SVM algorithm)
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
FaceRec
- 分别用基于PCA+SVM和PCA+Adaboost 两种算法进行对200张人脸图片进行识别。(200 face images are identified by two algorithms based on PCA+SVM and PCA+Adaboost.)
matlab
- 用于脑电信号分析的matlab算法，对数据进行PCA处理及SVM分类。(The matlab algorithm for EEG signal analysis performs PCA processing and SVM classification on data.)
贝叶斯人脸识别
- Pattern-Recognition-and-Machine-Learning-master,项目包括使用贝叶斯分类器的字符识别，基于GMM的图像分割，使用PCA的人脸识别和具有径向基函数的多类SVM分类器(Pattern-Recognition-and-Machine-Learning-master)
ML_SVM-master
- 算法功能是SVM分类，使用PCA降维处理，一个文件是直接分类，另一个是降维后分类(Classification using SVM algorithm)