Learning Data Conditions for Resolution Improvement Using UAV Data

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. R...

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Bibliographic Details
Published in2020 Joint 11th International Conference on Soft Computing and Intelligent Systems and 21st International Symposium on Advanced Intelligent Systems (SCIS-ISIS) pp. 1 - 2
Main Authors Matsui, Kai, Shirai, Hikaru, Kageyama, Yoichi, Yokoyama, Hiroshi
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.12.2020
Subjects
Lakes
machine learning
Remote sensing
resolution improvement
Training
Training data
unmanned aerial vehicle
Unmanned aerial vehicles
Water quality
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Summary: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.
DOI:10.1109/SCISISIS50064.2020.9322761