Abstract
In the current age of widespread application of artificial intelligence (AI) across various facets of life, satellite remote sensing is no outlier. Thanks to the ongoing enhancements in the spatial and temporal resolutions of satellite images, they are emerging as invaluable assets in areas such as land-use analysis, meteorology, change detection, and beyond. Accurate analysis and classification at various levels of hyperspectral images (HSIs) and multispectral remote sensing images (RSIs) are essential for extracting valuable insights from these datasets.
Original language | English |
---|---|
Pages (from-to) | 7212-7215 |
Number of pages | 4 |
Journal | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Volume | 17 |
DOIs | |
Publication status | Published - 19 Mar 2024 |
Bibliographical note
© 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, seehttps://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords
- Atmospheric Science
- Computers in Earth Sciences
ASJC Scopus subject areas
- Computers in Earth Sciences
- Atmospheric Science