Remote Sensing Image Classification Exploiting Multiple Kernel Learning

被引：15

作者：

Cusano, Claudio ^{[1
]}

Napoletano, Paolo ^{[2
]}

Schettini, Raimondo ^{[2
]}

机构：

[1] Univ Pavia, Dept Elect Comp & Biomed Engn, I-27100 Pavia, Italy

[2] Univ Milano Bicocca, Dept Informat Syst & Commun, I-20126 Milan, Italy

来源：

IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2015年 / 12卷 / 11期

关键词：

Multiple kernel learning (MKL); remote sensing image classification; SCENE;

D O I：

10.1109/LGRS.2015.2476365

中图分类号：

P3 [地球物理学]; P59 [地球化学];

学科分类号：

0708 ; 070902 ;

摘要：

We propose a strategy for land use classification, which exploits multiple kernel learning (MKL) to automatically determine a suitable combination of a set of features without requiring any heuristic knowledge about the classification task. We present a novel procedure that allows MKL to achieve good performance in the case of small training sets. Experimental results on publicly available data sets demonstrate the feasibility of the proposed approach.

引用

页码：2331 / 2335

页数：5

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