Learning Data Conditions for Resolution Improvement Using UAV Data

Learning Data Conditions for Resolution Improvement Using UAV Data
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使用无人机数据学习数据条件以提高分辨率

DOI：
10.1109/scisisis50064.2020.9322761
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发表时间：
2020
期刊：
2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS)
影响因子：
--
通讯作者：
Hiroshi Yokoyama
Hiroshi Yokoyama
中科院分区：
--
文献类型：
--
作者：
Kai Matsui;H. Shirai;Y. Kageyama;Hiroshi Yokoyama

文献摘要

被引文献

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本研究探讨一种利用遥感影像可见光范围及其波段比来改善影像分辨率的方法。本文通过无人机数据的波段比，考察了学习数据的条件，以提高分辨率改进方法的精度。对于测试数据中72.2%的条带比，使用具有大标准差的数据集获得的结果比使用具有小标准差的数据集获得的结果具有更高的准确度。
This study investigates a resolution improvement method using the visible range and its band ratio of remote sensing data. In this paper, we examined the conditions of learning data to improve the accuracy of the resolution improvement method through the band ratio of unmanned aerial vehicle data. Results obtained using the dataset with a large standard deviation had greater accuracy than those using the dataset with a small standard deviation for 72.2 % of the band ratio in the test data.