搜索资源列表
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2下载：
K均值算法，Matlab实现，输入分类数，实现分类-K means algorithm, Matlab implementation, enter the number of classifications to achieve classification
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此软件的功能是对遥感图像进行非监督分类。实现算法是k均值-This software is a remote sensing image for non-supervised classification. K-means algorithm implementation are
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c#下实现图像颜色k均值聚类
将像素点颜色分类并合并-c# implementation of color image k-means clustering to classification of color pixels and merge
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基于OpenCV的二元吗，实现了划分随机分布点集的K-均值算法。按照类别分组的输入样本顺序输出包含样本类别索引的数组labels(i)，存储在样本矩阵的第i行中。-Based on the binary OpenCV吗, implementation of the demarcation point set of randomly distributed K-means algorithm. Input in accordance with the type of packet contains
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实现了小波的图像量化，包括均匀量化，WSQ标准量化，k均值矢量量化，附简明pdf报告。-Implementation of wavelet image quantification, including the uniform quantization, WSQ standards for quantification, k means vector quantization, with a concise pdf report.
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基于K-Means的纹理图像分割，利用k-means方法实现对于纹理的图像分割-K-Means-based texture image segmentation using the k-means method implementation for texture image segmentation
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矢量量化算法的C语言实现：LBG(K-均值)聚类算法，在欧几里的距离基础上用LBG算法将输入向量聚类。-Vector quantization of C language implementation algorithm:LBG (k-means) clustering algorithm, in several European based on the distance with LBG algorithm will input vector clustering.
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基于c++对模式识别中K均值算法进行实现，可以读取不同波段数，并且实现对地物的分类效果。代码简单易行。-K-means algorithm in pattern recognition based on the c++ implementation, can read the band number and classification of surface features. The code is simple.
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Nister（2006）等人的层次聚类算法，按照多线程k-means方法进行多线程层次聚类，程序中代码对SIFT特征进行聚类。开发环境：vs2010-Implementation of hierarchical k-means, proposed by Nister et al, 2006. This is a multi-thread implementation of k-means and multi-thread implementation of the hierarchical me
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图像分割中K-means聚类算法的matlab实现-Image segmentation in the K-means clustering algorithm matlab implementation
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em算法计算混合高斯模型的参数估计，极大似然，EM算法用于K均值问题的参数估计。MATLAB实现有代码-em algorithm Gaussian mixture model parameter estimation, maximum likelihood parameter estimation for K-means problem EM algorithm. MATLAB implementation code
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自己实现的K均值聚类程序，有比较详细的注释-My implementation of K-means clustering procedure, with detailed notes
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自己实现的，模糊C均值聚类的代码，在K-mean上添加了隶属度矩阵。注释详细，方便理解算法步骤-my implementation, Fuzzy C-Means clustering code in the K-mean adding a membership matrix. Notes detailed, easy to understand algorithm steps
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SIFT等局部特征的词袋模型实现。包括K-means聚类，直方图特征的形成，以及KNN分类。-SIFT local features such as word bag model implementation. Including K-means clustering to form histogram features, and KNN classification.
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isodata算法的matlab实现,其中还附带K均值算法的源码实现。提供数据供大家验证-isodata algorithm matlab implementation, which also comes with K-means algorithm source code implementation. Provides data validation for everyone
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视频图像的人群密度检测，多种人群密度场景下人群计数算法：
算法功能:建立图像特征和图像人数的数学关系
算法输入:训练样本图像1,2…K
算法输出:模型估计参数 ，参考图像
算法流程：1)对训练样本图像进行分块处理(算法1.1)；
2)通过算法1.2，计算训练样本各个对应分块的ALBP特征归一化，再用K-means算法(可使用opencv等算法库实现，不再描述其算法)，将图像块分成k(k<K)类，获取k(k<K)个聚类中心，即为参考图像；
3)对分块的图像进行与
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图像K均值聚类，使用DIB类实现，整体比较简单-Image K-means clustering, using DIB class implementation, the overall relatively simple
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主要是K-Means算法的实现，可以直接执行，其中图片的载入用到opencv，其他均为C++源码。-Mainly K- Means algorithm implementation, which can be d directly, the images load use opencv, other are c++ source code.
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K-means聚类函数，训练，多维特征，纯C语言实现。-K- means clustering function, training, multidimensional characteristics, pure C language implementation.
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python实现用SIFT+K-MEANS+SVM图片分类(Python implementation with SIFT + K-MEANS + SVM picture classification)
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