期刊文献+

网格环境下分布式SVM遥感图像分类器模型研究 被引量:1

Distribute image classification model of RS based on grid and SVM method
下载PDF
导出
摘要 为了充分利用网格技术分布式、高性能、协同共享的能力,设计了一种基于网格和支持向量机的分布式图像分类器模型,采用网格计算技术,统筹网络运算资源,结合支持向量机在有限样本统计分类中的优势,探索网格技术在图像分类中的应用。以对遥感图像目标物体的特征提取为例,实现基于分布式计算的图像分类过程,基于.net环境的实验结果表明,该模型提高了数据密集型图像分类速度和处理效率。 Distributed image classification model based on grid and support vector machine is put forward in this paper to make full use of grid characteristic,such as distribution,high-performance and collaborative sharing capabilities etc.New model utilizes grid computing technology,plans as a whole of network computing resources,combines with statistic classification advantage of support vector machine in finite sample space, probes into application of grid computation technology in image classification.Tak- ing characteristic extraction of interesting ground object from RS(Remote Sensing) images as the example,image classification process based on distribution computation is implemented.Experimental results based on .Net environment show that new model improves classification speed and efficiency of data-intensive images.
出处 《计算机工程与应用》 CSCD 北大核心 2009年第5期193-195,206,共4页 Computer Engineering and Applications
基金 国家自然科学基金(No.40473029)~~
关键词 网格技术 遥感 图像分类 支持向量机 grid technology Remote Sensing(RS) image classification support vector machine(SVM)
  • 相关文献

参考文献9

  • 1Foster I,Kesselman C.The grid:blueprint for a new computing infrastructure[M].San Francisco,Calif:Morgan Kaufmann Publishers,1999.
  • 2惠文华.基于支持向量机的遥感图像分类方法[J].地球科学与环境学报,2006,28(2):93-95. 被引量:46
  • 3王建芬,曹元大.支持向量机在大类别数分类中的应用[J].北京理工大学学报,2001,21(2):225-228. 被引量:35
  • 4Foster I.The grid:a new infrastructure for 21st century seienc[J].Physics Today, 20002,55 (2) : 42-47.
  • 5Cristianini N,Shawe-Taylor J.An introduction to support vector machines and other kernel-based learning methods [M].New York: Cambridge University Press,2000.
  • 6HSU C W,LIN C J.A comparison of methods for multi2class sup2port vector machines[J].IEEE Transaction on Neural Network, 2002,13(2) :415-425.
  • 7Chang C C,Lin C J.LIBSVM:a library for support vector machines [EB/OL]. ( 2001 ).http://www.csie.ntu.edu.tw/-cjlin/libsvm.
  • 8Gao Juan.Artificial neural network principle and simulation example[M].BeiJing: China Machine Press, 2007 : 93-98.
  • 9Yu ZhiHui, Chen Yu,Liu Peng.Grid Computing[M].BeiJing:Tsinghua University Press,2002.

二级参考文献10

共引文献79

同被引文献2

引证文献1

二级引证文献17

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部