Machine Learning-Assisted Denoising of Raman Spectral Remote Sensing Data for Improved Land Use Mapping
Noise present in remote sensing data creates obstacles to proper land use and land cover (LULC) classification methods. The paper evaluates machine learning (ML) denoising methods that adapt Raman spectroscopy’s spectral te... | Find, read and cite all the research you need on Tech Science Press
Authors
- Jerome G. Gacu (ORCID: https://orcid.org/0000-0003-1577-7552)
- Fawad Salam Khan (ORCID: https://orcid.org/0009-0005-7014-9470)
- Cris Edward F. Monjardin (ORCID: https://orcid.org/0000-0003-3688-4402)
- Kevin Lawrence M. de Jesus (ORCID: https://orcid.org/0000-0002-7474-0090)
- Noman Hasany
- Muhammad Khurram (ORCID: https://orcid.org/0000-0001-6199-6364)
- Sabeur Abid
Publication Details
- Journal
- Revue internationale de géomatique
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/rig.2025.067026
- Primary Topic
- Remote-Sensing Image Classification
- Type
- article
- Field-Weighted Citation Impact
- 0.00