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인공위성 자료를 이용한 Faster R-CNN 기반 태풍 식별 및 강도․중심위치 산출Predicting the Intensity and the Center Location of Typhoons based on Faster R-CNN using Satellite Images

Other Titles
Predicting the Intensity and the Center Location of Typhoons based on Faster R-CNN using Satellite Images
Authors
이선화이수봉이정환한성원
Issue Date
2019
Publisher
대한산업공학회
Keywords
Deep Learning; Object Detection; Convolutional Neural Network; Typhoon Intensity and Center Estimation
Citation
대한산업공학회지, v.45, no.5, pp.439 - 450
Indexed
KCI
Journal Title
대한산업공학회지
Volume
45
Number
5
Start Page
439
End Page
450
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/70685
DOI
10.7232/JKIIE.2019.45.5.439
ISSN
1225-0988
Abstract
Locating the center and predicting the intensity of typhoons are critical issues to prevent damages caused bythem. In this paper, we propose two models based on Faster R-CNN for predicting the intensity and the centerlocation of typhoons via satellite images without pre-processing; one of the models utilizes an only single-channeland the other uses whole four channels. The biggest advantage of proposed models is that it can produce both thecenter coordinates and the class of the intensity regardless of the number of typhoons occurred, which never havebeen studies yet. Compared to the single-channel model, multi-channel model achieves higher typhoon detection ratethan single-channel model since it can extract various aspects of features from multiple channels through CNNbackbone network.
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