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A novel framework of detecting convective initiation combining automated sampling, machine learning, and repeated model tuning from geostationary satellite data File File

Han, Daehyeon , Lee, Juhyun , Im, Jungho , Sim, Seongmun , Lee, Sanggyun , Han, Hyangsun

Article Issue Date2019-06 View53
Deep learning-based monitoring of overshooting cloud tops from geostationary satellite data File

Kim, Miae , Lee, Junghye , Im, Jungho

Article Issue Date2018-04 View32
Detection and monitoring of forest fires using Himawari-8 geostationary satellite data in South Korea File File

Jang, Eunna , Kang, Yoojin , Im, Jungho , Lee, Dong-Won , Yoon, Jongmin , Kim, Sang-Kyun

Article Issue Date2019-02 View41
Detection of tropical overshooting cloud tops using himawari-8 imagery File File

Kim, Miae , Im, Jungho , Park, Haemi , Park, Seonyoung , Lee, Myong-In , Ahn, Myoung-Hwan

Article Issue Date2017-07 View57
Icing detection over East Asia from geostationary satellite data using machine learning approaches File File

Sim, Seongmun , Im, Jungho , Park, Sumin , Park, Haemi , Ahn, Myoung Hwan , Chan, Pak-wai

Article Issue Date2018-04 View46
Improved Ocean-Fog Monitoring Using Himawari-8 Geostationary Satellite Data Based on Machine Learning With SHAP-Based Model Interpretation File File

Sim, Seongmun , Im, Jungho

Article Issue Date2023-08 View33
Improving Short-Term Prediction of Ocean Fog Using Numerical Weather Forecasts and Geostationary Satellite-Derived Ocean Fog Data Based on AutoML File File

Sim, Seongmun , Im, Jungho , Jung, Sihun , Han, Daehyeon

Article Issue Date2024-07 View47
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