| 2019-12-10 | A big data-driven model for water quality estimation with high spectral and spatial resolution imagery | Pyo, JongCheol; Duan, Hongtao; Baek, Sangsoo; Jean, Taeyun; Kim, Moon Sung; Kwon, Yongsung; Lee, Hyuk; Cho, Kyung Hwa | CONFERENCE | 502 |
| 2019-11 | A convolutional neural network regression for quantifying cyanobacteria using hyperspectral imagery | Pyo, JongCheol; Duan, Hongtao; Baek, Sangsoo; Kim, Moon Sung; Jeon, Taegyun; Kwon, Yong Sung; Lee, Hyuk; Cho, Kyung Hwa | ARTICLE | 1144 |
| 2022-04 | A novel method for micropollutant quantification using deep learning and multi-objective optimization | Yun, Daeun; Kang, Daeho; Jang, Jiyi; Angeles, Anne Therese; Pyo, JongCheol; Jeon, Junho; Baek, Sang-Soo; Cho, Kyung Hwa | ARTICLE | 308 |
| 2019-12-09 | An enhanced water quality module of the SWMM model for evaluating Low Impact Development (LID) in Urban area | Baek, Sangsoo; Ligaray, Mayzonee; Pyo, JongCheol; Park, Jong-Pyo; Kang, Joo-Hyon; Chnn, Jong A; Cho, Kyung Hwa; Hong, Seokmin | CONFERENCE | 541 |
| 2020-03 | An Integrative Remote Sensing Application of Stacked Autoencoder for Atmospheric Correction and Cyanobacteria Estimation Using Hyperspectral Imagery | Pyo, JongCheol; Duan, Hongtao; Ligaray, Mayzonee; Kim, Minjeong; Baek, Sangsoo; Kwon, Yong Sung; Lee, Hyuk; Kang, Taegu; Kim, Kyunghyun; Cha, YoonKyung; Cho, Kyung Hwa | ARTICLE | 1746 |
| 2022-02 | Analysis of micropollutants in a marine outfall using network analysis and decision tree | Baek, Sang-Soo; Yun, Daeun; Pyo, JongCheol; Kang, Daeho; Cho, Kyung Hwa; Jeon, Junho | ARTICLE | 426 |
| 2022-11 | Application of airborne hyperspectral imagery to retrieve spatiotemporal CDOM distribution using machine learning in a reservoir | Kim, Jinuk; Jang, Wonjin; Kim, Jin Hwi; Lee, Jiwan; Cho, Kyung Hwa; Lee, Yong-Gu; Chon, Kangmin; Park, Sanghyun; Pyo, JongCheol; Park, Yongeun; Kim, Seongjoon | ARTICLE | 485 |
| 2019-10-30 | Application of drone-based hyperspectral imagery and vertical cumulative pigment concentration for cyanobacterial pigment estimation | Kwon, Yong Sung; Pyo, JongCheol; Kwon, Yong-Hwan; Duan, Hongtao; Cho, Kyung Hwa; Park, Yongeun | CONFERENCE | 457 |
| 2021-11 | Application of Machine Learning for eutrophication analysis and algal bloom prediction in an urban river: A 10-year study of the Han River, South Korea | Ly, Quang Viet; Nguyen, Xuan Cuong; Lê, Ngoc C.; Truong, Tien-Dung; Hoang, Thu-Huong T.; Park, Tae Jun; Maqbool, Tahir; Pyo, JongCheol; Cho, Kyung Hwa; Lee, Kwang-Sik; Hur, Jin | ARTICLE | 472 |
| 2017-11-17 | Chlorophyll-a and Phycocyanin estimation with optimization of bio-optical algorithm in inland waters in Korea | Pyo, JongCheol; Pachepsky, Yakov; Baek, Sang Soo; Kwon, YongSeong; Kim, MinJeong; Lee, Hyuck; Park, Sanghyun; Cha, YoonKyung; Ha, Rim; Nam, Gibeom; Park, Yongeun; Cho, Kyung Hwa | CONFERENCE | 327 |
| 2016-02 | Chlorophyll-a concentration estimation using three difference bio-optical algorithms, including a correction for the low-concentration range: the case of the Yiam reservoir, Korea | Pyo, JongCheol; Ha, SeongHyeon; Yakov A. Pachepsky; Lee, Hyuk; Ha, Rim; Nam, Gibeom; Kim. Moon S.; Im, Jungho; Cho, Kyung Hwa | ARTICLE | 1062 |
| 2020-11-13 | Convolutional neural network for estimating vertical profiles of harmful cyanobacteria using drone-borne hyperspectral image in lake water | Hong, Seok Min; Baek, Sang-Soo; Yun, Daeun; Kwon, Yong-Hwan; Pyo, JongCheol; Cho, Kyung Hwa | CONFERENCE | 540 |
| 2021-09 | Cyanobacteria cell prediction using interpretable deep learning model with observed, numerical, and sensing data assemblage | Pyo, JongCheol; Cho, Kyung Hwa; Kim, Kyunghyun; Baek, Sang-Soo; Nam, Gibeom; Park, Sanghyun | ARTICLE | 300 |
| 2021-10 | Deep Learning for Simulating Harmful Algal Blooms Using Ocean Numerical Model | Baek, Sang-Soo; Pyo, JongCheol; Kwon, Yong Sung; Chun, Seong-Jun; Baek, Seung Ho; Ahn, Chi-Yong; Oh, Hee-Mock; Kim, Young Ok; Cho, Kyung Hwa | ARTICLE | 410 |
| 2019-10 | Deep neural networks for modeling fouling growth and flux decline during NF/RO membrane filtration | Park, Sanghun; Baek, Sang-Soo; Pyo, JongCheol; Pachepsky, Yakov; Park, Jongkwan; Cho, Kyung Hwa | ARTICLE | 902 |
| 2021-05 | Designing a marine outfall to reduce microbial risk on a recreational beach: Field experiment and modeling | Kim, Minjeong; Ligaray, Mayzonee; Kwon, Yong Sung; Kim, Soobin; Baek, Sangsoo; Pyo, JongCheol; Baek, Gahyun; Shin, Jingyeong; Kim, Jaai; Lee, Changsoo; Kim, Young Mo; Cho, Kyung Hwa | ARTICLE | 385 |
| 2021-07 | Developing a cloud-based toolbox for sensitivity analysis of a water quality model | Kim, Soobin; Kwon, Yong Sung; Pyo, JongCheol; Ligaray, Mayzonee; Min, Joong-Hyuk; Ahn, Jung Min; Baek, Sang-Soo; Cho, Kyung Hwa | ARTICLE | 534 |
| 2016-10-25 | Developing a SWAT Sub-Module for Simulating Dynamics of Cyanobacteria, Green algae, and Diatom | Pyo, JongCheol; Pachepsky, Yakov A; Lee, Hyuk; Cha, YoonKyung; Park, Yongeun; Cho, Kyung Hwa | CONFERENCE | 314 |
| 2020-01 | Drone-based hyperspectral remote sensing of cyanobacteria using vertical cumulative pigment concentration in a deep reservoir | Kwon, Yong Sung; Pyo, JongCheol; Kwon, Yong-Hwan; Duan, Hongtao; Cho, Kyung Hwa; Park, Yongeun | ARTICLE | 975 |
| 2022-01 | Drone-borne sensing of major and accessory pigments in algae using deep learning modeling | Pyo, JongCheol; Hong, Seok Min; Jang, Jiyi; Park, Sanghun; Park, Jongkwan; Noh, Jae Hoon; Cho, Kyung Hwa | ARTICLE | 365 |
