Taegu Kang

Machine learning approaches to identify hydrochemical processes and predict drinking water quality for groundwater environment in a metropolis

An interpretable XGBoost-SHAP machine learning model for reliable prediction of mechanical properties in waste foundry sand-based eco-friendly concrete

Deep learning-based retrieval of cyanobacteria pigment in inland water for in-situ and airborne hyperspectral data