%0 Journal Article
%T Improved support vector machine and classification for remotely sensed data<br>改进的P-SVM支持向量机与遥感数据分类
%A ZHANG Rui
%A MA Jian-wen
%A <br>张 睿
%A 马建文
%J 遥感学报
%D 2009
%I 
%X In this paper, the P-SVM algorithm was introduced into multi-spectral/high-spatial resolution remotely sensed data classification and it is applied to classification of ASTER satellite data and ADS40 aerial digital data. The experiments indicate that the P-SVM is at least competitive with the standard SVM algorithm in classification accuracy of remotely sensed data and the time needed is less.
%K SVM
%K P-SVM
%K multi-spectral/high-spatial resolution remotely sensed data
%K classification<br>SVM
%K P-SVM
%K 多光谱/高分辨率遥感数据
%K 遥感数据分类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=A8799F5B31C7F974C52A400E11274978&yid=DE12191FBD62783C&vid=FC0714F8D2EB605D&iid=38B194292C032A66&sid=A48DE16C07AAAB06&eid=D0E8F9CBDBE0070C&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=36