Fine classification of rice fields in high-resolution remote sensing images
Author:
Publisher
Springer Science and Business Media LLC
Link
https://www.nature.com/articles/s41598-024-71394-3.pdf
Reference31 articles.
1. Bin Rahman, A. R. & Zhang, J. Trends in rice research: 2030 and beyond. Food Energy Secur. 12(2), e390 (2023).
2. Manjunath, K., More, R. S., Jain, N., Panigrahy, S. & Parihar, J. Mapping of rice-cropping pattern and cultural type using remote-sensing and ancillary data: A case study for South and Southeast Asian countries. Int. J. Remote Sens. 36(24), 6008–6030 (2015).
3. Hajjar, M. J., Ahmed, N., Alhudaib, K. A. & Ullah, H. Integrated insect pest management techniques for rice. Sustainability 15(5), 4499 (2023).
4. Khan, S. D., Basalamah, S. & Lbath, A. Weed-Crop segmentation in drone images with a novel encoder–decoder framework enhanced via attention modules. Remote Sens. 15(23), 5615 (2023).
5. Weiss, M., Jacob, F. & Duveiller, G. Remote sensing for agricultural applications: A meta-review. Remote Sens. Environ. 236, 111402 (2020).
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