搜索资源列表
SpPCA
- 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码,子模式主成分分析首先对原始图像分块,然后对相同位置的子图像分别建立子图像集,在每一个子图像集内使用PCA方法提取特征,建立子空间。对待识别图像,经相同分块后,分别将子图像向对应的子空间投影,提取特征。最后根据最近邻原则进行分类。
PCA_basedFaceRecognitionSystem2
- 基于PCA的人脸识别的matlab程序,有需要的可以看看。
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- 人脸识别matlab源代码基于pca方法
TDPCA2
- pca 算法的matlab实现 与大家一起分享
trainList
- PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the
feret
- PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the fi
fc
- PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the fi
createDistMat
- PCA人脸识别 This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database. Images are not preprocessed and it is up to the user to preprocess the images as wanted, not changing the fi
pcalda
- 基于\"pca+lda+粗糙集+模糊神经网络\"的人脸识别程序,在matlab上可直接运行
face_recognition
- PCA的人脸识别方法 Matlab 环境
1087
- pca+svm源代码(matlab) matlab代码,pca进行特征提取,svm进行分类
FailurePrediction
- matlab PCA应用于TE数据进行检测 包括SPE统计量计算,以及SPE和T方控制限的计算。
IPCA_JC_1
- 一种增量的人脸识别算法——增量PCA学习算法(matlab实现)
PCA_JC
- 经典人脸识别算法——PCA(Matlab实现)
pca2
- 基于主元分析(pca)的elman,rbf神经网络的matlab程序,运算时间短,程序简单
topoplot
- 基于采集的脑电导联信号,用matlab去噪和伪迹,最后绘制脑地形图。 去噪文件夹: FastICA_25文件夹为 fastICA函数;pca为pca 函数; av_sub伪迹减法去噪; ica_step1,ica_step2&pca 为ica与pca的去噪程序; wave_entro为小波熵的计算程序; topoplot为地形图函数; topo为画地形图程序;eloc32,eloc16为函数调用32导/16导的头皮电极分布位置 get_txt将采集的脑
FaceRec
- pca人脸识别matlab源码,其中提供了详细的步骤说明
rpca
- 基于人脸检测的pca算法的matlab程序
Untitled
- 人脸识别算法PCA的可执行程序,识别率为88.5%,为matlab平台程序,大家共享吧
pc_evectors
- 用matlab编写的找两个输入量之间的主要特征向量,主要方法采用PCA经典算法.-using Matlab prepared for the volume between two input of the main features of Vector, mainly using PCA classical algorithm.