基于机器学习的高、低分辨率图像融合方法改进目标分类

NAECON 2014 - IEEE National Aerospace and Electronics Conference Pub Date : 2014-06-24 DOI:10.1109/NAECON.2014.7045802

R. Ilin

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引用次数: 1

摘要

本研究利用高分辨率图像来提高低分辨率图像的分类精度。该方法基于被称为LUPI的机器学习范式——“使用特权信息学习”。在这篇文章中，LUPI范式在来自Caltech 101数据集的图像上进行了演示。

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

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.

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NAECON 2014 - IEEE National Aerospace and Electronics Conference

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