搜索资源列表
基于pca+lda+粗糙集+模糊神经网络的人脸识别
- 各种算法用于人脸识别，各个算法的识别率都不错，有lda,pca等算法(Various algorithms are used for face recognition, and the recognition rate of each algorithm is good. There are algorithms such as LDA, PCA and so on)
FaceRecognition
- 基于主成分分析的人脸识别，应用K-L变换作特征处理(Face recognition based PCA)
PCA&2DPCA (1)
- pca和2dpca的MATLAB人脸识别。并且使用orl人脸数据库进行测试(PCA and 2DPCA's MATLAB face recognition. And use the ORL face database to test)
face-SVM
- 用PCA和SVM实现人脸识别，是经典的人脸识别Python代码(Face recognition using PCA and SVM)
face-KNN
- 用PCA算法和KNN算法实现人脸识别，参数可以自己调整(The PCA algorithm and the KNN algorithm are used to realize the face recognition, and the parameters can be adjusted by themselves)
face-Bayes-GaussianNB
- 用贝叶斯中的高斯类库实现人脸识别，结合PCA算法实现(Face recognition using the Gauss class library in Bayes, combined with PCA algorithm)
face-Bayes-BernoulliNB
- 用贝叶斯中的努伯利类实现人脸识别，结合PACK算法实现(Bayesian face recognition in Nuboli, combined with PACK algorithm)
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)
FaceRecognition
- 采用PCA方法实现是脸识别，并附带人脸库(The implementation of the PCA method is face recognition with a face Library)
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
FPGA_hslogic_face
- FPGA代做，通过matlab实现PCA人脸识别算法，并计算识别率(n the FPGA generation, the PCA face recognition algorithm is realized by MATLAB and the recognition rate is calculated.)
第 07 章 基于主成分分析的人脸二维码识别
- 用MATLAB编写的基于PCA的人脸识别(PCA-based face recognition written in MATLAB)
PCA_based Face Recognition System
- 基于主成分分析pca的人脸识别matlab源码，用的是orl库(Face recognition matlab source code based on PCA)
FaceWaveANNDemo
- 基于小波变换和PCA面部识别，基于小波和神经网络的简单有效的人脸识别源代码。(Wavelet transform and PCA face recognition,Simple and Effective Source Code for Face Recognition Based on Wavelet and Neural Networks.)
eigenface-master
- 人脸识别，运用PCA主成分分析进行识别，orl人脸数据库，40个人(Face recognition PCA algorithm)
PCA+SVM
- 采用经典的ORL人脸数据集，利用PCA进行进行降维，然后用SVM进行数据集的分类和训练。上传文件内包含libSVM3.2安装包(The classical ORL face dataset is used for dimension reduction by PCA, and then SVM is used to classify and train the dataset.)
基于PCA的人脸识别
- 主成分分析法(principal conponent analysis, PCA)也叫Hotelling变换或特征脸法，是基于 K-L变换基础上研发得到的。该方法的核心是能够降低图像空间的维度，具体做法是将原始的数据通过某种线性变换从高维度空间转变到低维度空间中，这些数据彼此不相关，根据贡献率选取最大的前一部分，使原数据具有最大的变化量，对后面的图像也向这个空间投影，然后比较它们之间的距离来确定类别关系。PCA方法的缺点是对光照问题比较敏感。
人脸识别
- 人脸特征提取matlab源码。适用于人脸识别的matlab实现。(Facial feature extraction matlab source code. It is suitable for matlab implementation of face recognition.)
人脸图像特征提取与对比
- NMF、PCA-人脸图像特征抽取与对比，图像识别，主成分分析(Face image feature extraction and comparison, image recognition, principal component analysis)
PCA-SVM-face
- 使用MATLAB语言，基于主成分分析和支持向量机进行人脸识别(MATLAB face detection)