| Drought assessment and monitoring through blending of multi-sensor indices using machine learning approaches for different climate regions S Park, J Im, E Jang, J Rhee Agricultural and Forest Meteorology 216, 157-169, 2016 | 299 | 2016 |
| Detection of deterministic and probabilistic convection initiation using Himawari-8 Advanced Himawari Imager data S Lee, H Han, J Im, E Jang, MI Lee Atmospheric Measurement Techniques 10 (5), 1859, 2017 | 60 | 2017 |
| Estimation of fugacity of carbon dioxide in the East Sea using in situ measurements and Geostationary Ocean Color Imager satellite data E Jang, J Im, GH Park, YG Park Remote Sensing 9 (8), 821, 2017 | 29 | 2017 |
| Estimation of water quality index for coastal areas in Korea using GOCI satellite data based on machine learning approaches E Jang, J Im, S Ha, S Lee, YG Park 대한원격탐사학회, 2016 | 12 | 2016 |
| Developing data-driven models for quantifying Cochlodinium polykrikoides using the Geostationary Ocean Color Imager (GOCI) YS Kwon, E Jang, J Im, SH Baek, Y Park, KH Cho International Journal of Remote Sensing 39 (1), 68-83, 2018 | 10 | 2018 |
| Machine learning approaches to drought monitoring and assessment through blending of multi-sensor indices for different climate regions S Park, J Im, E Jang, H Yoon, J Rhee EGU General Assembly Conference Abstracts 16, 2014 | 3 | 2014 |
| GOCI 위성영상과 기계학습을 이용한 한반도 연안 수질평가지수 추정 E Jang, J Im, S Ha, S Lee, YG Park | 1* | 2016 |
| Developing Data-driven models for quantifying Cochlodinium polykrikoides in Coastal Waters Y Kwon, E Jang, J Im, S Baek, Y Park, K Cho EGU General Assembly Conference Abstracts 19, 6098, 2017 | | 2017 |
| Machine Learning Approaches for Detection of Convective Initiation (CI) using Geostationary Satellite and Weather Radar Data S Lee, J Im, E Jang 한국기상학회 학술대회 논문집, 182-183, 2015 | | 2015 |
