Description: 现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。-existing algebra feature extraction method using a majority of the peacekeepers, First images will be converted into one-dimensional vector, and then principal component analysis (PCA), Fisher Linear Discriminant Analysis (LDA), Fisherfaces audits principal component analysis (KPCA), and other selected characteristics, then use the appropriate classification for classification. Victoria against an excessive dimension method, calculation, covariance matrix is often inadequate singular matrix, a two-dimensional image feature extraction method, a small amount of covariance matrix is usually reversible, and the recognition rate higher. Platform: |
Size: 2513 |
Author:小弟 |
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Description: 现有的代数特征的抽取方法绝大多数采用一维的方法，即首先将图像转换为一维向量，再用主分量分析（PCA）,Fisher线性鉴别分析（LDA）,Fisherfaces式核主分量分析（KPCA）等方法抽取特征，然后用适合的分类器分类。针对一维方法维数过高，计算量大，协方差矩阵常常是奇异矩阵等不足，提出了二维的图像特征抽取方法，计算量小，协方差矩阵一般是可逆的，且识别率较高。-existing algebra feature extraction method using a majority of the peacekeepers, First images will be converted into one-dimensional vector, and then principal component analysis (PCA), Fisher Linear Discriminant Analysis (LDA), Fisherfaces audits principal component analysis (KPCA), and other selected characteristics, then use the appropriate classification for classification. Victoria against an excessive dimension method, calculation, covariance matrix is often inadequate singular matrix, a two-dimensional image feature extraction method, a small amount of covariance matrix is usually reversible, and the recognition rate higher. Platform: |
Size: 2048 |
Author:小弟 |
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Description: 线性判别分析（LDA）是一种较为普遍的用于特征提取的线性分类方法。但是将LDA直接用于人耳识别会遇到维数问题和“小样本”问题。人们经过研究，通过多种途径解决了这两个问题并实现了基于LDA的人耳识别。文章对几种基于LDA的人耳识别方法做了理论上的比较和实验数据的支持，这些方法包括Fisherears、DLDA、VDLDA及VDFLDA。实验结果表明VDFLDA是其中最好的一种方法
-Linear Discriminant Analysis (LDA) is a more common linear feature extraction for classification. LDA but used directly in the human ear to identify problems encountered dimension and the Platform: |
Size: 2129920 |
Author:冷福 |
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Description: 线性鉴别技术是一种较好的分类技术,本程序采用了基于PCA与LCA的人脸识别方法使人脸识别效率得到提高-Linear identification technology is a better classification techniques, the procedures for the use of PCA and LCA-based face recognition method of face recognition efficiency Platform: |
Size: 1024 |
Author:黄璞 |
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Description: 针对灰度图像，提出一种基于知识的人脸检测方法。
提出了一种给予支持向量机的人脸检测方法。
提出了一种基于小波分解的LDA人脸识别方法。
提出了一种基于小波和DCT的人脸识别方法。
提出了一种机遇CEDT和支持向量机的人脸分类和识别方法。
-For gray-scale images, a knowledge-based face detection methods. A support vector machine method of face detection. A wavelet decomposition of the LDA-based face recognition methods. A wavelet and DCT-based face recognition methods. A CEDT opportunities and support vector machine classification and face recognition. Platform: |
Size: 7113728 |
Author:yanyan |
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Description: 一个基于LDA的分类程序，对于初学者有很大的帮助-LDA-based classification procedures, for the great help for beginners Platform: |
Size: 1024 |
Author:吕晋普 |
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Description: 用于对USPS数据进行分类的各种分类器，用于对多维采样点进行无监督分类。可根据类别数修改分类器，模式识别作业的部分代码。
-USPS data for the various classification categories, for sampling points on the multi-dimensional non-supervised classification. Can be modified in accordance with several types of classifiers, pattern recognition part of the operating code. Platform: |
Size: 5560320 |
Author:王兵 |
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Description: Chesnokov Yuriy写的人脸检测库，内容涵盖肤色检测、运动估计、SVM分类、PCA/LDA/ICA特征提取以及神经网络分类器等。-The article 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 reduction/projection and final NN classification Platform: |
Size: 463872 |
Author:刘子木 |
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Description: 捷克理工大学Hlavac教授和Franc博士提供的统计模式识别Matlab工具箱的最新版本V2.09，在原有版本基础上进行了一些修改和完善。它包括现有模式识别的大部分方法，比如SVM，PCA，LDA等。我采用其中的SVM方法进行了人体下肢假肢SEMG信号的分类，效果不错。希望能对大家有帮助。-Statistical Pattern Recognition Toolbox for Matlab (C) 1999-2008, Version 2.09. It includs a number of ways for paater classification, such as SVM, PCA, LDA, etc. I hope it is helpful for readers. Platform: |
Size: 5998592 |
Author:Mountain |
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Description: 包括pca和lda两个文件，先用pca降维后进行lda进行分类，用于人脸识别，实验结果很好。-It includes 2 files pca and lda. After the dimensionality reduction of pca, use lda for classification in face recognition. It has a very good experimental results. Platform: |
Size: 1024 |
Author:wangyuru |
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Description: 二维线性鉴别分析(2DLDA)算法能有效解决线性鉴别分析(LDA)算法的“小样本”效应，支持向量机
(SVM)具有结构风险最小化的特点，将两者结合起来用于人脸识别。首先，利用小波变换获取人脸图像的低频分量，忽
略高频分量：然后，用2DLDA算法提取人脸图像低频分量的线性鉴别特征，用“一对多”的SVM 多类分类算法完成人脸
识别。基于ORL人脸数据库和Yale人脸数据库的实验结果验证了2DLDA+SVM算法应用于人脸识别的有效性。-”Small sample size”problem of LDA algorithm can be overcome by two—dimensional LDA f 2DLDA)，and
Support Vector Machine(SVM)has the characteristic of structural risk minimization．In this paper，two methods were
combined and used for face recognition．Firstly，the original images were decomposed into high—frequency and low—frequency
components by Wavelet Transform(WT)．The high—frequency components were ignored，while the low—frequency components
can be obtained．Then．the liner discriminant features were extracted by 2DLDA，and”one VS rest”。strategy of SVMs for
muhiclass classification was chosen to perform face recognition． Experimental results based on ORL f Olivetti Research
Laboratory1 face database and Yale face database show the validity of 2DLDA+SVM algorithm for face recogn ition． Platform: |
Size: 236544 |
Author:费富里 |
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Description: 用于文本分析和分类的pLSA(Probability Latent Semantic Analysis)的Matlab算法，含有测试数据及算法原理介绍。也可用于图像分析。相比原来的版本，增加了示例程序demo.m，以实现可视化效果，用户更容易使用和理解pLSA算法。-For text analysis and classification of pLSA (Probability Latent Semantic Analysis) of the Matlab algorithm with test data and algorithm theory description. Can also be used for image analysis. Compared to the original version, an increase of sample programs demo.m, to achieve the visual effect, the user can more easily use and understand the algorithm. Platform: |
Size: 302080 |
Author:Tang Ketan |
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Description: a good algorithm for classification performance improvement (use PCA and LDA respectively and then implement the resulted data set into your classifier) Platform: |
Size: 1024 |
Author:nazila |
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Description: LDA文本分类技术综述，对LDA进行了全面细致的概述，适合文本分类初学者-Review of the LDA text classification techniques, LDA comprehensive and detailed overview, suitable for text classification beginners Platform: |
Size: 1145856 |
Author:许明 |
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Description: LDA:线性判别分析方法。用于实现线性数据降维。采用K近邻分类器对数据进行分类-LDA: linear discriminant analysis method. Used to achieve linear data dimensionality reduction. Using K-nearest neighbor classifier for data classification Platform: |
Size: 1024 |
Author:彭霞 |
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Search - LDA for classification