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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
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
ImageClustering.rar
- 本程序实现了K均值(HCM)算法，ISODATA算法，模糊C均值(FCM)，模糊阈值法等对遥感影像的分割。,This program implements K means (HCM) algorithm, ISODATA algorithm, fuzzy C means (FCM), fuzzy threshold law of remote sensing image segmentation.
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-Mean
- 遥感影像K均值分类算法，针对bmp彩色图像。VC++6.0编程实现。-K means of remote sensing image classification algorithm for bmp color images. VC++6.0 programming.
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-means
- k-means 经典算法，c语言实现，要的下载-classical k-means algorithm, c language, it is necessary to download
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
K
- K均值算法-分类器-有效抑制边缘点影响-简单有效-K-means algorithm- Classifier- effectively inhibiting the impact of edge points- simple and effective
fuzme_matlab
- Fuzy K Means 快速图象分割Fuzy K Means Fuzy K Means-Fuzy K Means Fuzy K MeansFuzy K MeansFuzy K MeansFuzy K MeansFuzy K Means
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
K均值对图像进行聚类分析
- 用k-means算法对图像进行聚类，适合于初学者(K-means algorithm for clustering images, suitable for beginners)
k-means
- 实现k均值聚类算法，可以使用彩色图像，通过随机初始化聚类中心，完成聚类(The K-means clustering algorithm can use color images to initialize cluster centers randomly and accomplish clustering.)
K-means图像识别
- 利用K-means对图像进行聚类，识别。您可以设置参数达到更好的识别效果(Using K-means to cluster and identify images.You can set parameters to achieve better recognition results)
K-means
- 对图像用k-means算法进行处理，得到效果更好的图像(Processing the image with k-means algorithm)
PCA-K
- 该算法主要包含PCA算法和K-Means聚类算法，用于SAR变化检测,包含数据图片。(The algorithm mainly includes PCA algorithm and K-means clustering algorithm for SAR change detection, including data images.)