%0 Journal Article
%T Tensor-based learning machine for remotely sensed image target detection<br>张量分类算法的遥感影像目标探测
%A ZHANG Lefei
%A ZHANG Liangpei
%A TAO Dacheng
%A <br>张乐飞
%A 张良培
%A 陶大程
%J 遥感学报
%D 2010
%I 
%X This paper proposes a new way to detect the targets in remote sensing images based on the tensor learning machine (TLM). This method is based on tensor and tensor algebra. To utilize the multidimensional data of the remote sensing image, the vector-based learning machine is generalized to the tensor-based learning machine which accepts tensors as input, then the convex optimization theory and the alternating projection procedure are used to get the solution of the TLM. TLM is tested to target detection using the hyperspectral remote sensing data and high resolution remote sensing data. The experiments demonstrate the effectiveness of the proposed method, by comparing TLM with support vector machine, the tensor learning machine can keep a high probability of successful detection and reduce the false alarm.
%K tensor
%K convex optimization
%K supervised learning
%K target detection<br>张量
%K 最优化理论
%K 监督学习
%K 目标探测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=A41A70F4AB56AB1B&jid=F926358B31AC94511E4382C083F7683C&aid=AE9AD4A7480F10B9C81DFE7AE80051FF&yid=140ECF96957D60B2&vid=F3583C8E78166B9E&iid=38B194292C032A66&sid=E3D3D8D1B650AE1E&eid=92DA076AF6760FAC&journal_id=1007-4619&journal_name=遥感学报&referenced_num=0&reference_num=13