Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

Singh, Deveshwar; Choi, Yunsoo; Park, Jincheol; Salman, Ahmed K.; Sayeed, Alqamah; Song, Chul Han

doi:10.1016/j.atmosres.2024.107283

Atmospheric Research

2024

DOI: 10.1016/j.atmosres.2024.107283

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Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

Deveshwar Singh,

Yunsoo Choi,

Jincheol Park

et al.

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Cited by 4 publications

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Deep-BCSI: A deep learning-based framework for bias correction and spatial imputation of PM2.5 concentrations in South Korea

Cited by 4 publications

References 38 publications

Temporal CNN-based 72-h ozone forecasting in South Korea: Explainability and uncertainty quantification

Temporal CNN-based 72-h ozone forecasting in South Korea: Explainability and uncertainty quantification

Deep learning bias correction of GEMS tropospheric NO2: A comparative validation of NO2 from GEMS and TROPOMI using Pandora observations

Innovative approaches for accurate ozone prediction and health risk analysis in South Korea: The combined effectiveness of deep learning and AirQ+

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