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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
在matlab下的k-均值聚类进行图像分类分割处理
- 在matlab下的k-均值聚类进行图像分类分割处理,In matlab under the k-means clustering for image classification be dealt with separately
K_means_color_segmentation.rar
- 用k-means 做彩色图像分割，分类数可选,Using k-means to do color image segmentation, classification number of optional
kmeans
- 基于matlab的图像k均值算法，实现对一副彩色图像进行分割。-Matlab image based on k means algorithm, to realize a color image segmentation.
kmeans
- k均值图像分割，经典的图像分割方法，算法简单，效果好。-k-means image segmentation
pc
- 利用相位一致性提取图像边缘，K-means聚类后区域生长进行图像分割，附参考论文。-Using phase coherence image edge extraction, K-means clustering image after region growing segmentation, attached reference paper.
K-MEANS
- 基于K-MEAN的图像分割,方便实用，对于图像处理的研究生很有参考价值的-watershed segmentation on matlab
99273866Ms_segmenter
- 用matlab实现的图像k均值分割，很好用的，以经过验证-Using matlab to achieve k-means image segmentation, well used to a proven
K_average
- k均值聚类或者成为均值聚类，用于对各个数据进行分类-k-means clustering or a means clustering for the classification of the various data
kmeans-image-segmentation
- K均值算法实现图像的分割，分割效果可以达到预期的效果-K-means algorithm to achieve image segmentation, segmentation results can be achieved the desired results
KMEANS
- 使用一种改进的k均值进行图像处理，方便使用-The use of a k-means for improved image processing, user-friendly
kmeans-image-segmentation
- K均值 很好用的K均值代码 -K-means K-means used in a very good code
k_means
- k-均值聚类法用于各种图像的聚类、分割问题，希望可以对您有利-k-means clustering method for a variety of image clustering, segmentation
k_means_Gray
- 对于灰度图的 k均值算法实现 matlab代码-Gray graphics k-means matlab code
a
- 对于彩色图像的 k均值算法的matlab代码 文件置于c盘根目录-Colored graphics k-means algorithm matlab code
Kmeans_grayimage
- 简单的灰度图像的K均值聚类分割，Matlab实现-gray image segmentation using K-means clustering by matlab.
K-Means-Matlab
- k-means聚类算法的matlab代码 截图的 想用还是自己手打吧-k-means clustering algorithm matlab code screenshot or their own hands to fight it.
K-mean
- K-means算法是很典型的基于距离的聚类算法，采用距离作为相似性的评价指标，即认为两个对象的距离越近，其相似度就越大(K-means algorithm is a typical distance based clustering algorithm. The distance is used as the evaluation index of similarity, that is, the closer the distance between the two objects, the
K-Means PCA降维
- K-Means算法,不要求建立模型之后对结果进行新的预测，没有相应的标签，只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the character
基于 K-means 聚类算法的图像区域分割
- 基于K-means聚类算法的图像区域分割(Image region segmentation based on K-means clustering algorithm)