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Jungho Im

Showing results (1-10 of 18) with videos related to

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Iscience|May 27, 2024
Enhancing tropical cyclone intensity forecasting with explainable deep learning integrating satellite observations and numerical model outputsJuhyun Lee, Jungho Im, Yeji Shin
Journal of Hazardous Materials|February 4, 2025
Comprehensive 24-hour ground-level ozone monitoring: Leveraging machine learning for full-coverage estimation in East AsiaYejin Kim, Seohui Park, Hyunyoung Choi, et al.
Journal of Hazardous Materials|July 11, 2025
Bridging temporal gaps: AI-based temporal downscaling of biweekly NH<sub>3</sub> to daily scale with spatial transferabilitySaman Malik, Eunjin Kang, Yoojin Kang, et al.
Environmental Pollution (Barking, Essex : 1987)|May 10, 2022
Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast AsiaSeohui Park, Jungho Im, Jhoon Kim, et al.
The Science of the Total Environment|April 17, 2025
Developing a novel Temporal Air-quality Risk Index using LSTM autoencoder: A case study with South Korean air quality dataHyerim Park, Wonho Sohn, Eunjin Kang, et al.
Environmental Pollution (Barking, Essex : 1987)|February 11, 2023
Retrieval of hourly PM<sub>2.5</sub> using top-of-atmosphere reflectance from geostationary ocean color imagers I and IIHyunyoung Choi, Seonyoung Park, Yoojin Kang, et al.
Iscience|October 25, 2023
Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in SeoulCheolhee Yoo, Jungho Im, Qihao Weng, et al.
Nature Communications|May 11, 2026
Global patterns of urban heat shaped by climate and morphologySiwoo Lee, Cheolhee Yoo, Bokyung Son, et al.
The Science of the Total Environment|September 25, 2025
Aerosol optical depth retrieval from Geostationary Environment Monitoring Spectrometer (GEMS): Advancing the first hyperspectral geostationary air quality mission using deep learningHyunyoung Choi, Seohui Park, Jungho Im, et al.
Marine Pollution Bulletin|July 25, 2025
Robust daily satellite sea surface salinity reconstruction using deep learning in low-salinity coastal regionsSihun Jung, So-Hyun Kim, Eunna Jang, et al.
Pageof 2

Showing results (1-10 of 18) with videos related to

Sort By:
Pageof 2
Iscience|May 27, 2024
Enhancing tropical cyclone intensity forecasting with explainable deep learning integrating satellite observations and numerical model outputsJuhyun Lee, Jungho Im, Yeji Shin
Journal of Hazardous Materials|February 4, 2025
Comprehensive 24-hour ground-level ozone monitoring: Leveraging machine learning for full-coverage estimation in East AsiaYejin Kim, Seohui Park, Hyunyoung Choi, et al.
Journal of Hazardous Materials|July 11, 2025
Bridging temporal gaps: AI-based temporal downscaling of biweekly NH<sub>3</sub> to daily scale with spatial transferabilitySaman Malik, Eunjin Kang, Yoojin Kang, et al.
Environmental Pollution (Barking, Essex : 1987)|May 10, 2022
Geostationary satellite-derived ground-level particulate matter concentrations using real-time machine learning in Northeast AsiaSeohui Park, Jungho Im, Jhoon Kim, et al.
The Science of the Total Environment|April 17, 2025
Developing a novel Temporal Air-quality Risk Index using LSTM autoencoder: A case study with South Korean air quality dataHyerim Park, Wonho Sohn, Eunjin Kang, et al.
Environmental Pollution (Barking, Essex : 1987)|February 11, 2023
Retrieval of hourly PM<sub>2.5</sub> using top-of-atmosphere reflectance from geostationary ocean color imagers I and IIHyunyoung Choi, Seonyoung Park, Yoojin Kang, et al.
Iscience|October 25, 2023
Diurnal urban heat risk assessment using extreme air temperatures and real-time population data in SeoulCheolhee Yoo, Jungho Im, Qihao Weng, et al.
Nature Communications|May 11, 2026
Global patterns of urban heat shaped by climate and morphologySiwoo Lee, Cheolhee Yoo, Bokyung Son, et al.
The Science of the Total Environment|September 25, 2025
Aerosol optical depth retrieval from Geostationary Environment Monitoring Spectrometer (GEMS): Advancing the first hyperspectral geostationary air quality mission using deep learningHyunyoung Choi, Seohui Park, Jungho Im, et al.
Marine Pollution Bulletin|July 25, 2025
Robust daily satellite sea surface salinity reconstruction using deep learning in low-salinity coastal regionsSihun Jung, So-Hyun Kim, Eunna Jang, et al.
Pageof 2