搜索资源列表
pcaBPneuralnetwork
- 用主成分分析与神经网络进行人脸的识别 文件是整个的ＭＡＴＬＡＢ数据文件-using principal component analysis and neural networks face identification document is the entire data file MATLAB
icafsvm.rar
- 用于人脸识别的模糊独立成分分析+主成分分析，用模糊支持向量机进行的分类。,Fuzzy Face Recognition for independent component analysis+ principal component analysis, using fuzzy support vector machine classification.
Face-Recognition
- 基于主成份分析(PCA)的人脸识别算法MATLAB程序的实现。机器视觉的作业，内附人脸识别的matlab程序，和人脸库，还有作业的详细要求，以及格式示例和部分参考文献。-Based on principal component analysis (PCA) of the face recognition algorithm MATLAB program implementation. Machine vision operations, included face recognition mat
neatestface
- 人脸识别matlab程序，pca主成分分析法，采用最小距离决策-Face recognition matlab program, pca principal component analysis method, using a minimum distance between the decision-making
KernelPrincipalComponentAnalysis
- 用于图像识别的核主分量识别子程序，不包括分类器程序-For image recognition to identify the nuclear principal component subprogram does not include classification program
ORL_faces
- 人脸识别：使用PCA方法，即主成分分析，区分人脸和非人脸。主要用于随即过程大作业。-Face Recognition: Using the PCA method, that is, principal component analysis, the distinction between face and non-human face. Then the process used mainly for large operations.
pca
- pca算法的matlab实现 主成分分量分析可用于数据的降维和模式识别问题 -pca algorithm matlab component analysis to achieve the principal component can be used for data dimensionality reduction and pattern recognition problem
kernel-ica1_1
- 基于核函数的主分量分析法源代码，可用于人脸识别-Kernel-based principal component analysis source code, can be used for face recognition
ImprovedPCAFaceRecognitionAlgorithm
- 摘要：主成分分析（PCA）的人脸识别算法，以减少的特征向量是涉及到对抽象的特点，改进了主成分分析（一）iUumination算法的变化影响酶原sed.The方法是基于上减低与正常化其相应的标准差的特征向量元素相关联的大特征值的特征向量的影响力的想法。耶鲁大学和耶鲁大学面临的数据库面对数据库B是用来验证-Abstract：In principal component analysis(PCA)algorithms for face recognition，to reduce the influen
FERET_PCA
- 在matlab中实现主成分分析方法，并使用FERET库的灰度图像进行测试-This package implements basic Principal Component Analysis in Matlab and tests is with grayscale portion of the FERET database.
PCADR
- 用于特征降维人脸识别等多元数据分析的主分量分析投影的Matlab代码实现。-For feature reduction and other multivariate data analysis, face recognition principal component analysis projection of the Matlab code implementation.
PCA
- 基于主成分分析的人脸识别，本程序给出了N次重复实验后各维数的识别率-Principal Component Analysis(PCA)for face recognition
2DPCA
- 基于二维主成分分析的人脸识别,本程序在ORL人脸库上进行了测试-Two-dimensional Principal Component Analysis for Face Recogntion.
licenseplatelocation
- 一种多车牌定位方法，该方法综合利用边缘检 测、连通域分析、倾斜矫正等多种方法,解决了复杂背景中定位难的问题-A multi-plate location method, which combined with an edge detection, connected component analysis, tilt correction and other methods to solve the complex problem of difficulties in the context
partiald
- 基于主分量分析的人脸识别算法试验，用matlab编写-Face recognition based on principal component analysis algorithm for testing
face-recognition
- pca又称主成分分析，主要用来提取图像的主要成分，作为特征提取一个重要算法，将其用于人脸识别-pca, also known as principal component analysis, mainly used to extract the main component of the image, as a key feature extraction algorithm, be used in face recognition
weifen
- 主分量分析实现人脸识别人脸识别matlab源代码，应用主分量分析（PCA）实现了人脸识别。-Principal component analysis of face recognition
matlab-main-component-analysis
- matlab主成分分析，含完整主成分分析方法以及matlab源代码-matlab principal component analysis, including principal component analysis and the complete source code matlab
LPR
- 提供一种最基础的车牌识别程序，需进行以下几个基本的步骤：车牌图像预处理；车牌定位，定位图片中的车牌位置；车牌字符分割，把车牌中的字符分割出来；车牌字符识别，把分割好的字符进行识别，最终组成车牌号码。(To provide a basic license plate recognition program, the following basic steps need to be carried out: image preprocessing of license plate; Location
41972254PCA_ORL
- 代码是关于主成分分析的人脸识别，使用orl人脸图像集(The code is about principal component analysis of face recognition using ORL face image set)