In this paper, an improved K means clustering algorithm is presented to accelerate clustering process with more and more classes becoming stable by judging with neighbor centers nearest to the pixel.

  • 改进后的K-means聚类算法使类内像素只通过和相邻的聚类中心进行距离计算来聚类,由于随着算法的迭代进行,大量类的状态基本固定,因此使得聚类速度不断加快。
  • 来源:互联网摘选更新时间:2026-04-04 12:51:11

  • 重点词汇
  • algorithmn.运算法则;演算法;计算程序;
  • presentedvt.& vi.(动词present的过去式及过去分词形式);表示"展示;展现;出示";
  • clusteringn.聚类;
  • centersn.中心( center的名词复数 );(球队的) 中锋;中心区;中枢;
  • neighborn.<美>邻居,邻国;
  • toprep. 向,朝着;到;关于;属于;
  • more and more越来越;越来越 ...;日益;
  • judgingvt.& vi.审判,评判(judge的现在分词形式);
  • 相关例句
1、

Using K Means which can automatically cluster trajectories, a new algorithm based on trajectory space similarity distance is presented, and it is applied to classify trajectory.

应用K均值自动聚类算法,提出了一种新的基于轨迹空间相似距离的轨迹分类算法,对以上获得的有效轨迹进行分类。

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2、

In this paper, we use direct classification and K means algorithm to distinguish the high cloud, meddle cloud, low cloud and earth ′ s surface.

应用模式识别中区域聚类法即最近邻简单试探法和K-均值聚类算法来完成高云、中云、低云和地表的区分。

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3、

The results illustrate that the best centroids initialization in K means clustering is to select vectors characterized the structure of the dataset.

结果表明:若对基因表达数据进行K-均值聚类分析,最好采用能反映数据结构特征的向量对质心进行初始化。

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4、

Experimental results show that this new classifier can realize high quality unsupervised image classification, which outperforms the traditional K means classifier.

实验结果表明,该种分类器能很好地实现对纹理粗糙程度模式的无监督分类,其分类性能要明显好于传统的K均值分类器。

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5、

Results Fuzzy K means clustering algorithm can segment white matter, gray matter and CSF better from the MR head images.

结果模糊K-均值聚类算法能很好地分割出磁共振颅脑图像中的灰质、白质和脑脊液。

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6、

A data matrix based on the signal gain of cellular networks and some criterion functions are designed for K means clustering.

在聚类分解中,以测试点信号增益矩阵构造聚类分解数据,并给出了收敛判定函数和相似度计算方法。

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7、

Fuzzy K means Clustering Algorithm and It's Application Study in Segmentation of MR Head Images

模糊K-均值聚类算法及其在磁共振颅脑图像分割中的应用研究

互联网摘选

8、

It also resolves the initial parameter problem of K means algorithm.

而且解决了K-means聚类的参数选择问题。

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9、

Analysis on K means Clustering Algorithm and Its Application in Teaching Quality of Teacher

K-means聚类算法分析及在教师授课质量评价中的应用

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10、

Genetic k Means Algorithm for Clustering of Large Scale Vector Space

大矢量空间聚类的遗传k-均值算法

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11、

Cluster analysis based on K means and immune algorithm

基于K均值和免疫算法的聚类分析

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12、

Automatic Text Categorization Based on K-Nearest Neighbor

基于K-最近距离的自动文本分类的研究

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13、

K-nearest neighbor classifier and BP neural network classifier are designed for the acoustic target classification.

并设计了KNN和改进的BP神经网络两种分类器。

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14、

The third step directly classifies the ship as one of the five types with k-nearest neighbor method.

第三步使用k-近邻法直接将舰船目标分配到五类中的一类。

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15、

An algorithm for reverse k-nearest neighbor queries based on M-tree in spatial network databases

空间网络数据库中基于M-tree索引的反最近邻查询算法

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16、

K-Nearest Neighbor Nonparametric Regression for probability forecasting with its applications

K近邻非参数回归概率预报技术及其应用

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17、

K-Nearest Neighbor Nonparametric Estimation Bootstrap Model for Weather Probability Forecasting

概率天气预报的K近邻非参数估计仿真模型

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18、

K-Nearest Neighbor Classification Based on Semantic Distance

基于语义距离的K-最近邻分类方法

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19、

The performance of K-Nearest Neighbor classification algorithm depends on the selection of distance metrics.

K-NN(K-Nearest Neighbor)分类算法的结果依赖于距离度量的选取。

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20、

Mining against-expectation patterns by two ways including k-nearest neighbor graph and correlation analysis.

通过最近邻居图[3]和相关分析两种方法挖掘反期望模式。

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