搜索资源列表
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
homework
- 使用基于PCA+KNN算法实现的人脸识别，本算法的优点在于使用的是基于2DPCA的方法，计算时间更短，效率更高。-PCA+ KNN-based face recognition algorithm, the advantage of this algorithm is based on the use of 2DPCA method in calculating the time is even shorter, more efficient.
LDA1
- 这是用pca lda knn进行分类的lda部分的代码-It is used to classify pca lda knn part of the code of lda
pca
- pca lda knn 进行分类的pca部分的代码-pca lda knn classification of the pca part of the code
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.
knn_bayes_pca_lda
- 课程设计源代码，实现功能在文档内有介绍。内含knn、bayes识别及pca、lda进行特征提取多种算法，运行参照readme。-The project source code.The realized function is introduced in the pdf document in the files including knn,bayes classification and pcd,lda feature extraction algorithms.Please read read
FaceRec_Final
- 5-fold cross valication for Face recognition using PCA, SVM and KNN.
llde_cmb
- 人脸检测一直是人们在研究的问题，流形学习用于人脸检测中的特征提取，用PCA与constructM进行降维，KNN分类器用于分类。取得非常好的效果。-Face detection has been the problem of people in the study, manifold learning for face detection feature extraction using PCA and constructM dimension reduction, KNN classifier
PCA
- 该算法主要是模式识别的分类算法，KNN 最近邻分类算法-The algorithm is pattern recognition classification algorithm, KNN nearest neighbor classification algorithm
Neural-Network
- This folder contains the following sub-folders which are essential in our project: 1.Raw Data All the raw data collected from Flagstaff hill, CMU Athletic Field, and Railroad on Neville St. 2.Filter Filter to rule out signal of Channel
pcaExpression
- openCV-C++代码，用PCA算法进行人脸主成分提取，并且用kNN算法进行实时表情识别。程序可以自己建立数据库并且进行识别，非常好用！附课程的作业报告。-openCV-C++ code, using PCA algorithm for face principal component extraction and real-time facial expression recognition algorithm with kNN. Program can create their own
fisher
- fisher准则的pca人脸识别程序example: 演示程序 creatData:生成数据 creatTrainLabelMat:生成数据标签 LDA:提取fisherface knnRecognition:knn分类器 knnsearch:knn搜索-Fisher criterion example: face recognition program PCA demonstration program CreatData: generat
PCA
- 对高维图像进行PCA和KNN分类器处理转换为低维图像(use PCA and KNN for high dimensional image)
tensorflow-knn-双向LDA
- 基于LDA的人脸降维，精度比二维LDA的要高，有一定的运用价值。(orl tensorflow LDA PCA)