| Estimation of heavy metals using deep neural network with visible and infrared spectroscopy of soil JC Pyo, SM Hong, YS Kwon, MS Kim, KH Cho Science of The Total Environment 741, 140162, 2020 | 110 | 2020 |
| Drone-borne sensing of major and accessory pigments in algae using deep learning modeling JC Pyo, SM Hong, J Jang, S Park, J Park, JH Noh, KH Cho GIScience & Remote Sensing 59 (1), 310-332, 2022 | 23 | 2022 |
| Monitoring the vertical distribution of HABs using hyperspectral imagery and deep learning models SM Hong, SS Baek, D Yun, YH Kwon, H Duan, JC Pyo, KH Cho Science of The Total Environment 794, 148592, 2021 | 21 | 2021 |
| Estimation of cyanobacteria pigments in the main rivers of South Korea using spatial attention convolutional neural network with hyperspectral imagery SM Hong, KH Cho, S Park, T Kang, MS Kim, G Nam, JC Pyo GIScience & Remote Sensing 59 (1), 547-567, 2022 | 14 | 2022 |
| Deep learning with data preprocessing methods for water quality prediction in ultrafiltration J Shim, S Hong, J Lee, S Lee, YM Kim, K Chon, S Park, KH Cho Journal of Cleaner Production 428, 139217, 2023 | 6 | 2023 |
| Automatic classification of microplastics and natural organic matter mixtures using a deep learning model S Lee, H Jeong, SM Hong, D Yun, J Lee, E Kim, KH Cho Water Research 246, 120710, 2023 | 6 | 2023 |
| Inland harmful algal blooms (HABs) modeling using internet of things (IoT) system and deep learning DH Kwon, SM Hong, A Abbas, JC Pyo, HK Lee, SS Baek, KH Cho Environmental Engineering Research 28 (1), 2023 | 6 | 2023 |
| Evaluating an on-line cleaning agent for mitigating organic fouling in a reverse osmosis membrane S Park, SM Hong, J Park, S You, Y Lee, E Kim, KH Cho Chemosphere 275, 130033, 2021 | 5 | 2021 |
| Autonomous calibration of EFDC for predicting chlorophyll-a using reinforcement learning and a real-time monitoring system SM Hong, A Abbas, S Kim, DH Kwon, N Yoon, D Yun, S Lee, ... Environmental Modelling & Software 168, 105805, 2023 | 3 | 2023 |
| Deep learning-based super-resolution for harmful algal bloom monitoring of inland water DH Kwon, SM Hong, A Abbas, S Park, G Nam, JH Yoo, K Kim, HT Kim, ... GIScience & Remote Sensing 60 (1), 2249753, 2023 | 1 | 2023 |
| Comparison of SWAT and a deep learning model in nitrate load simulation at the Tuckahoe creek watershed in the United States J Lee, D Kim, S Hong, D Yun, D Kwon, R Hill, Y Pachepsky, F Gao, ... EGU24, 2024 | | 2024 |
| Estimating Escherichia coli levels using drone-based RGB imagery and machine learning techniques S Hong, B Morgan, M Stocker, J Smith, M Kim, KH Cho, Y Pachepsky EGU24, 2024 | | 2024 |
| Deep learning-based efficient drone-borne sensing of cyanobacterial blooms using a clique-based feature extraction approach J Shin, G Lee, TH Kim, KH Cho, SM Hong, DH Kwon, JC Pyo, YK Cha Science of The Total Environment 912, 169540, 2024 | | 2024 |
| Predicting the distribution coefficient of cesium in solid phase groups using machine learning SM Hong, IH Yoon, KH Cho Chemosphere, 141462, 2024 | | 2024 |
| Evaluation of Machine Learning Algorithms for Predicting E. coli Concentrations using Drone-based RGB Images and Water Quality Data with Imbalanced Dataset S Hong, YA Pachepsky, B Morgan, M Stocker, MS Kim AGU23, 2023 | | 2023 |
| Predicting the Distribution Coefficients of Radionuclides Using Machine Learning IH Yoon, S Na, SM Hong, I Kim, I Kim, KS Jeong, KH Cho 한국방사성폐기물학회 학술논문요약집 21 (2), 350-350, 2023 | | 2023 |
| Developing a data-driven modeling framework for simulating a chemical accident in freshwater S Kim, A Abbas, JC Pyo, H Kim, SM Hong, SS Baek, KH Cho Journal of Cleaner Production 425, 138842, 2023 | | 2023 |
| Prediction of Distribution Coefficient of Cesium Using Machine Learning Models SM Hong, IH Yoon, KH Cho 한국방사성폐기물학회 학술논문요약집 21 (1), 330-330, 2023 | | 2023 |
| Application of Reinforcement Learning to Calibrate Cyanobacteria using Daily Water Quality Parameters in EFDC Model S Hong, K Hwa Cho, A Abbas, S KIM, DH Kwon, N Yoon, D Yun, S Lee AGU Fall Meeting Abstracts 2022, H15L-0942, 2022 | | 2022 |
| Enhancement of Spatial resolution with Deep Learning-based Super-Resolution models for Inland Harmful Algal Bloom (HABs) monitoring DH Kwon, S Hong, A Abbas, S Park, G Nam, JH Yoo, K Kim, JC Pyo, ... AGU Fall Meeting Abstracts 2022, H15J-0916, 2022 | | 2022 |
Kyung Hwa ChoKorea UniversityEmail confirmado em korea.ac.kr
