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: 灰度共生矩阵和灰度梯度共生矩阵的提取方式，是比较重要的纹理特征提取方法，用matlab实现的-co-occurrence matrix and GGCM extraction, is the more important Texture feature extraction methods, achieved using Matlab Platform: |
Size: 2048 |
Author:李明 |
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Description: 共生矩阵的实现及特征提取方法，里面包含了各个特征向量提取的子程序，可以在其他程序中直接调用。-co-occurrence matrix and the realization of feature extraction methods, each of which contains a feature vector extraction subroutine, the other procedures can be called directly. Platform: |
Size: 3072 |
Author:chenwei |
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Description: （1）应用9×9的窗口对上述图象进行随机抽样，共抽样200块子图象；
（2）将所有子图象按列相接变成一个81维的行向量；
（3）对所有200个行向量进行KL变换，求出其对应的协方差矩阵的特征向量和特征值，按降序排列特征值以及所对应的特征向量；
（4）选择前40个最大特征值所对应的特征向量作为主元，将原图象块向这40个特征向量上投影，所获得的投影系数就是这个子块的特征向量。
（5）求出所有子块的特征向量。
-(1) the application of 9 × 9 window of these images at random, a total sample of 200 sub-image (2) all sub-images according to out-phase into a 81-dimensional row vector (3) all 200 lines for KL transform vector, derived its corresponding covariance matrix of eigenvectors and eigenvalues, in descending order by eigenvalue and the corresponding eigenvector (4) a choice to 40 corresponding to the largest eigenvalue eigenvector as the PCA, the original image block to the 40 feature vectors on the projection, the projection coefficients obtained by this sub-block eigenvector. (5) calculated for all sub-block eigenvector. Platform: |
Size: 64512 |
Author:ly |
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Description: 对图像进行特征提取，得到其特征矩阵后方便用IHDR数进行存储，主要用于发育机器人方面-Image feature extraction, by its characteristic matrix IHDR after the number of user-friendly storage, mainly used for development of robotics Platform: |
Size: 4410368 |
Author:gikidy |
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Description: 非负矩阵分解技术（Nonnegtive Matrix Factorization 一种信号或图像的特征提取的方法，也可用于图像压缩 -Non-negative Matrix Factorization technique (Nonnegtive Matrix Factorization a signal or image feature extraction methods can also be used for image compression Platform: |
Size: 1024 |
Author:邹晶 |
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Description: 计算四个方向的灰度共生矩阵，将其作为纹理特征，是一种纹理特征提取算法。-Calculation of the four directions of Gray Level Co-occurrence matrix as texture features, is a kind of texture feature extraction algorithm. Platform: |
Size: 1024 |
Author:Owenli |
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Description: 基于非负矩阵分解（NMF）的人脸特征提取算法，NMF基本思想是找到一个线性子空间W，使的构成子空间的基本图像的像素点都是正值，而且人脸图像在子空间上的投影系数也是正数-Non-negative Matrix Factorization (NMF) of facial feature extraction algorithm, NMF basic idea is to find a linear sub-space W, so that the composition of sub-space of the basic image pixels are positive, and face image in the sub-space projection coefficient is positive Platform: |
Size: 1024 |
Author:李伟 |
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Description: Matlab程序独立打包与混合编程的研究
Matlab程序的独立打包指的是不借用其他语言的混合编
程方法， 而只使用Matlab本身提供的打包工具实现Matlab程序
在未安装Matlab的机器上运行的方法。-Matlab is a good large-scale numerical simulation software.the program run in an explain implementation mode.It has a lot of
feature,for example: Real-time debug window ,high-performance computing matrix ,Rich toolbox,etc. These feature make it into a
numerical computation and scientific research must-have software.Although the Matlab has many advantages, but it is very difficult to
complete the process from the environment to run matlab,the interface also features low efficiency.These shortincomings make us who
using it ,begin worry about the results of their own convenience can not be made public easily.This paper makes an analysis on matlab s
run mode,then make mixed-language programming methods between Matlab and VC,And how to improve the independence and
efficiency of Matlab program. Platform: |
Size: 124928 |
Author:zgc |
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Description: 灰度共生矩阵相关资料，包括生成灰度共生矩阵matlab代码，Matlab7工具箱中缺少的graycomatrix.m文件，以及一个通过灰度共生矩阵提取特征的matlab程序（共20多个特征），可以根据他的方法来从灰度共生矩阵中提取你需要的特征。-GLCM relevant information, including generating GLCM matlab code, Matlab7 toolbox graycomatrix.m missing documents, and a gray level co-occurrence matrix feature extraction through the matlab program (a total of more than 20 features), can be based on his method to extract from the GLCM features you need. Platform: |
Size: 11264 |
Author:Du |
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Description: 用于提取EMG/MMG/ECG信号的频谱分析的特征量MATLAB代码，采用的算法是非负分解（NNMF）。-This program is designed to extract the feature of EMG/MMG/ECG signal in hand motions via the non-negative matrix factorization algorithm. Platform: |
Size: 8192 |
Author:zy |
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Description: 为了更有效地提取图像的局部特征，提出了一种基于2维偏最小二乘法(two—dimensional partial least
square，2DPLS)的图像局部特征提取方法，并将其应用于面部表情识别中。该方法首先利用局部二元模式(1ocal
binary pattern，LBP)算子提取一幅图像中所有子块的纹理特征，并将其组合成局部纹理特征矩阵。由于样本图像
被转化为局部纹理特征矩阵，因此可将传统PLS方法推广为2DPLS方法，用来提取其中的判别信息。2DPLS方法
通过对类成员关系矩阵的构造进行相应的修改，使其适应样本的矩阵形式，并能体现出人脸局部信息重要性的差
异。同时，对于类成员关系协方差矩阵的奇异性问题，也推导出了其广义逆的解析解。基于JAFFE人脸表情库的
实验结果表明，该方法不但可以有效地提取图像局部特征，并能取得良好的表情识别效果。-To better the image of the local feature extraction, a partial least squares method based on 2D (two-dimensional partial least
square, 2DPLS) image local feature extraction method, and applied to facial expression recognition. In this method, use of local binary pattern (1ocal
binary pattern, LBP) operator extracts an image texture features of all sub-blocks, and their combination into the local texture feature matrix. As the sample image
Be translated into the local texture feature matrix, so the traditional PLS method can be generalized to 2DPLS method used to extract the identification information. 2DPLS method
Through the class membership matrix in the corresponding modifications to adapt the sample matrix, and can reflect the importance of face poor local information
Different. Meanwhile, members of the class covariance matrix of the singular relations issues, also derived the generalized inverse of the analytical solution. Based on the JAFFE facial expression database
Platform: |
Size: 315392 |
Author:MJ |
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Description: 基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。-Feature extraction of specified object is an
important preprocessing stage in machine vision
systems. In this paper, we present a novel hybrid
feature extraction method using PCNN (Pulse Coupled
Neural Network) and shape information. First, we use
PCNN firing map train to formulate object’s time
signature, then we use roundness of each firing map to
formulate object’s shape information vector, the final
feature matrix we got is combined time signature and
roundness. We take correlations as our judge criteria
in our experiments. It has been proved that the
algorithm is not sensitivity with the rotation, scaling
and translation of the object and is a useful method for
target recognition applications. Platform: |
Size: 1024 |
Author:wangxiaofei |
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Description: Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr-Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr Platform: |
Size: 3283968 |
Author:driftinwind |
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Description: 基于共生矩阵纹理特征提取，d=1,θ=0°,45°,90°,135°共四个矩阵,所用图像灰度级均为256-Co-occurrence matrix based texture feature extraction, d = 1, θ = 0 °, 45 °, 90 °, 135 ° total of four matrices, the use of gray-scale images are 256 Platform: |
Size: 1024 |
Author:ygliang30 |
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Description: matlab最全纹理特征代码，灰度共生矩阵软件自带，就不传了。里面有tamura六个参数，灰度梯度共生矩阵的纹理特征，还有熵。-matlab the best texture feature code, the GLCM software comes not passed. Tamura six parameters, the shades of gray co-occurrence matrix texture features, as well as entropy. Platform: |
Size: 5120 |
Author:张三 |
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Description: MATLAB 实现的概率矩阵分解，可以用于社交网络推荐，将评分矩阵分解为两个低维的用户和商品特征矩阵。代码中需要在load位置添加自己试验所需的数据集。-MATLAB realization probability matrix decomposition can be used for social networking recommendation, the scoring matrix is decomposed into two low dimensional feature matrix of users and commodities. The code you need to add their own data sets required for the test load position. Platform: |
Size: 3072 |
Author:小飞 |
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Description: 利用matlab提取出频域和时域信号的29个特征，主运行文件feature_extraction，fre_statistical_compute和time_statistical_compute分别提取频域和时域的特征，生成的29个特征保存在生成的feature矩阵中。(Using MATLAB to extract 29 features of frequency-domain and time-domain signals, the main running files feature extraction, frequency-domain and time-domain features are extracted respectively, and the 29 features are saved in the generated feature matrix.) Platform: |
Size: 8860672 |
Author:我爱骑单车 |
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Search - feature matrix matlab