[1]赵春晖,陈万海,万? 建.一种改进的多类支持向量机超光谱图像分类方法[J].智能系统学报,2008,3(1):77-82.
ZHAO Chun-hui,CHEN Wan-hai,WAN jian.An improved hyperspectral image classification method for? a multiclass support vector machine[J].CAAI Transactions on Intelligent Systems,2008,3(1):77-82.
点击复制
ZHAO Chun-hui,CHEN Wan-hai,WAN jian.An improved hyperspectral image classification method for? a multiclass support vector machine[J].CAAI Transactions on Intelligent Systems,2008,3(1):77-82.
一种改进的多类支持向量机超光谱图像分类方法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第1期
页码:
77-82
栏目:
学术论文—机器学习
出版日期:
2008-02-25
- Title:
- An improved hyperspectral image classification method for? a multiclass support vector machine
- 文章编号:
- 1673-4785（2008)01-0077-06
- 分类号:
- TN919.81
- 文献标志码:
- A
- 摘要:
- 支持向量机（SVM）是建立在统计学理论基础上的一种机器学习方法，用于解决二类分类问题，如何有效地将其推广到多类分类问题是一个正在研究的课题.总结了现有的主要的支持向量机多类分类算法，并在1a1 SVM分类算法基础上提出一种二次分类的方法 . 改良了惩罚因子，提高了不易分的类别之间的可分程度.通过对超光谱图像进行分类实验，结果表明该方法具有较高的分类精度.
- Abstract:
- SVM is a machine learning method developed on the basis of statistics theory and originally designed for binary classification problems. The most effe ctive way to extend it for multiclass classification is still an area of conside rable discussion. This paper presental a secondary classification method based o n 1a1 SVM classification algorithm after a general overview of typical method s for a multiclass SVM. Our method improves the penalty factors, so it enhances th e divisibility of classes that were difficult to classify. Experimental results o f hyperspectral image classification showed that the suggested multiclass SVM ha s higher classification precision.
- 参考文献/References:
-
［1］任建峰,郭 雷.多类支持向量机的自然图像分类［J］. 西北工业大学学报, 2005, 23（3） : 295298.
?REN Jianfeng, GUO Lei. Improving scene image classification with multiclass SVMs［J］. Journal of Northwestern Polytechnical University, 2005, 23（3）: 29 5298.
［2］HSU C W, LIN C J. A comparison of methods for multiclass support ve ctor machines［J］.IEEE Transactions on Neural Networks, 2002, 13(2): 415425
. ［3］刘志刚,李德仁,秦前清,等.支持向量机在多类分类问题中的推广［J］. 计算机工程与应用, 2004(7): 1013.
LIU Zhigang, LI Deren, QIN Qianqing,et al. An analytical overvie w of methods for multicategory support vector machines［J］. Computer Enginee ring and Applications, 2004(7): 1013.
［4］LANDGREBE D. Multispectral data analysis: a signal theory perspectiv e［R］. West Lafayette,USA: University, 1998.
［5］刘春红,赵春晖,张凌雁.一种新的高光谱遥感图像降维方法［J］.中国图像图形学报, 2005, 10（3）: 218222.
LIU Chunhong, ZHAO Chunhui, ZHANG Lingyan. A new method of hyperspectral r emote sensing image dimensional reduction［J］. Journal of Image and Graphic, 2 005, 10(3): 218222.
［6］赵英时.遥感应用分析原理与方法［M］. 北京: 科学出版社, 2003.
- 相似文献/References:
-
[1]王书舟,伞 冶.支持向量机的训练算法综述[J].智能系统学报,2008,3(6):467.
WANG Shu-zhou,SAN Ye.A survey on training algorithms for support vector machine[J].CAAI Transactions on Intelligent Systems,2008,3():467.
[2]陈小娥,陈昭炯.多类SVM在图像艺术属性分类中的应用研究[J].智能系统学报,2009,4(2):157.
CHEN Xiao-e,CHEN Zhao-jiong.An application of multiclass SVM in the classification of artistic attributes of images[J].CAAI Transactions on Intelligent Systems,2009,4():157.
[3]黄剑华,唐降龙,刘家锋,等.一种基于Homogeneity的文本检测新方法[J].智能系统学报,2007,2(1):69.
HUANG Jian-hua,TANG Xiang-long,LIU Jia-feng,et al.A new method for text detection based on Homogeneity[J].CAAI Transactions on Intelligent Systems,2007,2():69.
[4]张 亮,朱振峰,赵 耀,等.基于镜头的鲁棒视频广告检测[J].智能系统学报,2007,2(2):83.
ZHANG Liang,ZHU Zhen-feng,ZHAO Yao,et al.Video commercial detection based on the robustness of sho t[J].CAAI Transactions on Intelligent Systems,2007,2():83.
[5]杨志豪,洪 莉,林鸿飞,等.基于支持向量机的生物医学文献蛋白质关系抽取[J].智能系统学报,2008,3(4):361.
YANG Zhi-hao,HONG L i,L IN Hong-fei,et al.Extraction of information on prote in2prote in interaction from biomedical literatures using an SVM[J].CAAI Transactions on Intelligent Systems,2008,3():361.
[6]刘? 琚,乔建苹.基于学习的超分辨率重建技术[J].智能系统学报,2009,4(3):199.
LIU Ju,QIAO Jian-ping.Learningbased superresolution reconstruction[J].CAAI Transactions on Intelligent Systems,2009,4():199.
[7]刘 胜,李高云,江 娜.SVM性能的免疫鱼群多目标优化研究[J].智能系统学报,2010,5(2):144.
LIU Sheng,LI Gao-yun,JIANG Na.Multiobjective optimization of an immune fish swarm algorithm to improve support vector machine performance[J].CAAI Transactions on Intelligent Systems,2010,5():144.
[8]杨振兴,刘久富,孙 琳.不变量的程序潜在错误预测[J].智能系统学报,2010,5(4):327.
YANG Zhen-xing,LIU Jiu-fu,SUN Lin.Using invariants to predict the potential for errors in programs[J].CAAI Transactions on Intelligent Systems,2010,5():327.
[9]古丽娜孜,孙铁利,伊力亚尔,等.一种基于主动学习支持向量机哈萨克文文本分类方法[J].智能系统学报,2011,6(3):261.
GU Linazi,SUN Tieli,YI Liyaer,et al.An approach to the text categorization of the Kazakh language based on an active learning support vector machine[J].CAAI Transactions on Intelligent Systems,2011,6():261.
[10]何世钊,杨宣访,陈晓娟.支持向量机与BP网络在火灾图像探测上的比较[J].智能系统学报,2011,6(4):339.
HE Shizhao,YANG Xuanfang,CHEN Xiaojuan.Comparisons between a support vector machine and BP neural network for video image fire detection[J].CAAI Transactions on Intelligent Systems,2011,6():339.
备注/Memo
收稿日期：2007-06-06.
基金项目：
高等学校博士学科点基金资助项目(20060217021)；
黑龙江省自然科学基金资助项目(ZJG060601).
作者简介：
赵春晖，男，1965年生，教授，博士生导师.获省部级科技奖5项.主要研究方向为智能信息处理技术、图像处理.出版著作3部，发表论文200余篇.
?陈万海，男，1963年生，副教授，博士研究生.主要研究方向为超光谱遥感图像处理技术，发表论文18篇.
万 建，男，1980年生，博士研究生.主要研究方向为信号与图像处理，发表论文5篇.
通讯作者：赵春晖.E-mail:zhaochunhui@hrbeu.edu.cn.
更新日期/Last Update:
2009-05-10