Machine learning approach to fusion of high and low resolution imagery for improved target classification

被引：0
|
作者：
Ilin, Roman [1 ]
机构：
[1] Air Force Res Lab, Sensors Directorate, Wright Patterson AFB, OH 45433 USA
来源：
IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON 2014) | 2014年
关键词：
LUPI; SVM; Clustering; Object Classification;
D O I：
暂无
中图分类号：
V [航空、航天];
学科分类号：
08 ; 0825 ;
摘要：
this work utilizes high resolution images in order to improve the classification accuracy on low resolution images. The approach is based on the machine learning paradigm called LUPI - "Learning Using Privileged Information". In this contribution, the LUPI paradigm is demonstrated on images from the Caltech 101 dataset.
引用
收藏
页码：195 / 199
页数：5
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