搜索资源列表
SAR
- 以MSTAR为实验数据,对SAR影像进行杂波统计分析研究。利用高斯、瑞利、对数正态、LN、gamma函数模型对其拟合,通过K-S方法检验拟合精度-The MSTAR the experimental data, statistical analysis of SAR images of clutter. Gaussian, Rayleigh, lognormal, LN, gamma function model to its fitting, fitting by means of check
kmeans
- kmeans image segmentation Input: ima: grey color image k: Number of classes Output: mu: vector of class means mask: clasification image mask -kmeans image segmentation Input: ima: grey color image k: Numbe
FCM
- 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
mvqx177
- 用MFC开发的简单的k-means实现代码,原创啊()
exdluslve-yinker
- k-means算法,包括一个测试的4类的测试数据集,()
sgtxdwu
- K-MEANS聚类算法,以及PSO和QPSO算法改进K-MEANS算法,breastcancer数据验证了该分类模型的有效()
7018267
- KMEANS Trains a k means cluster model CENTRES KMEANS(CENTRES,()
MeanShift_Code
- meanshift、k-means算法图像分割对比(meanshift and k-means Image processing technology)
image_segmentation
- 使用k-means聚类实现多光谱图像分割,并配有高维视图查看聚类结果(Clustering algorithm for multispectral image segmentation)
automatic_image_segement
- 本文以k-means算法为背景,引入信息熵相关知识,从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时,会发生一定的过拟合现象,导致我们得不到预期的聚类数目。本文设计合理的合并准则,令模型简化,有效地消除过拟合现象,使得最后得到的聚类数目与预期符合。,设计合理的准则改进了图像的全自动分割方法,使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy