Detection of Air Pollution Using Hyperspectral Imaging
This study employed novel hyperspectral imaging (HSI) algorithm to quantify air pollution through spectral analysis of particulate matter (PM2.5) images. Two models, HSI-3DCNN and RGB-3DCNN, are trained, with HSI-3DCNN demonstrating a 7.75% average accuracy increase.
Authors
- Yu-Ming Tsao
- Hsiang‐Chen Wang (ORCID: https://orcid.org/0000-0003-4107-2062)
- Hôǹg Thái Nguyêñ (ORCID: https://orcid.org/0000-0002-1666-0666)
- Arvind Mukundan (ORCID: https://orcid.org/0000-0002-7741-3722)
- Riya Karmakai
- Song-Cun Lu
Institutions
- National Chung Cheng University (TW)
Publication Details
- Published
- 2024-08-04
- DOI
- https://doi.org/10.1109/cleo-pr60912.2024.10676637
- Primary Topic
- Air Quality Monitoring and Forecasting
- Type
- article
- Field-Weighted Citation Impact
- 0.00