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K均值聚类
- 对图像进行K均值聚类的程序
用matlab实现K均值聚类算法
- 用matlab实现K均值算法
K-均值聚类算法
- K-均值聚类算法，对数据进行聚类分析，可用于提取关键帧等。用matlab实现,K-means clustering algorithm, cluster analysis of data that can be used, such as key frame extraction. Using matlab to achieve
基于matlab的K均值聚类程序
- 基于matlab的K均值聚类程序。其中用IRIS数据进行验证，得到了很好的结果。文件中包含了演示后的结果图,Matlab-based K-means clustering procedure. Which use IRIS data verification, have had good results. File contains the results of the demonstration plan
k均值图像分割
- k均值方法，对图像进行分割，matlabt程序，希望对大家有所帮助
K-means_clustering_demo
- K-均值聚类算法 vc++图形演示程序-K-means clustering algorithm c++ demo program
K-Means
- K均值聚类算法 C++实现的K均值聚类算法。-K means clustering algorithm C++ Achieved K-means clustering algorithm.
k-mean k均值聚类程序
- k均值聚类程序，虽然matlab中也有自带的，但是这个速度不错。-program for k means used for cluster
K-means
- 简单实用的k均值聚类算法，可以实现多位向量的简单聚类-Simple and practical k-means clustering algorithm, can achieve more than a simple vector clustering
K-mean
- K均值算法： 给定类的个数K，将N个对象分到K个类中去， 使得类内对象之间的相似性最大，而类之间的相似性最小-K-means algorithm: the number of a given type of K, will be assigned to N objects of category K go, making the object category similarity between the largest, while the category of the simi
K-means_Matlab
- K-均值算法的Matlab源代码，比较简短-Matlab source code of K-means algorithm
k-means
- k均值聚类算法源码 聚类算法学习的实例功能-k-means cluster algorithm
k-centers
- 不同于k均值聚类的k中心聚类，2007年SCIENCE文章Clustering by Passing Messages Between Data Points 中的方法-Unlike k-means clustering of the k cluster centers, in 2007 SCIENCE article, Clustering by Passing Messages Between Data Points of the Method
K均值聚类
- K均值聚类算法图像分割，最传统的一种分割方法(K mean clustering segmentation)
K均值聚类在基于OpenCV的图像分割中的应用
- 介绍了传统的图像分割与K-均值聚类算法分割，然后利用OpenCV函数将其实现，并介绍了OpenCV中图像分割相关的基本函数。(This paper introduces the segmentation of traditional image segmentation and K- mean clustering algorithm, then uses OpenCV function to implement it, and introduces the basic functions of
k均值聚类
- 用VC++写的K均值聚类算法，可以直接使用(K mean clustering algorithm is written by VC++ , which can be used directly.)
k均值聚类算法
- 根据k均值聚类的原理，实现一些数字的聚类，但是具体类别数需要自己设置(Clustering of some numbers by K mean clustering)
K—均值聚类提取
- k均值聚类提取，适合学习。先将RGB图像转换到LAB空间，在LAB空间进行聚类分割。(K-means clustering is suitable for learning. First convert the RGB image to LAB space and perform clustering and segmentation in the LAB space.)
K均值聚类
- K均值聚类算法-对数据进行聚类分析，适合数据处理(k means clustering algorithm)
基于粒子群优化的k均值
- 基于粒子群优化的k均值，可以对实验对象进行定性分类(Based on the k-means of particle swarm optimization, the experimental objects can be qualitatively classified)