Development, performance evaluation and prediction of optimal operational conditions for a double-row sugarcane harvester using deep learning
- DOI
- 10.1038/s41598-025-30739-2
- Published
- 2025-12-01
- Container
- Scientific Reports
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-025-30739-2,
title = {Development, performance evaluation and prediction of optimal operational conditions for a double-row sugarcane harvester using deep learning},
author = {Abdallah Elshawadfy Elwakeel and Abdallah Zein Elden and Saad F. Ahmed and Sali Issa and Changyou Li and Khaled Abdeen Mousa Ali and Waleed M. Hanafy and Guma Ali and Fawaz Alzahrani and Atef Fathy Ahmed},
year = {2025},
journal = {Scientific Reports},
doi = {10.1038/s41598-025-30739-2},
url = {https://doi.org/10.1038/s41598-025-30739-2}
}RIS
TY - JOUR TI - Development, performance evaluation and prediction of optimal operational conditions for a double-row sugarcane harvester using deep learning AU - Abdallah Elshawadfy Elwakeel AU - Abdallah Zein Elden AU - Saad F. Ahmed AU - Sali Issa AU - Changyou Li AU - Khaled Abdeen Mousa Ali AU - Waleed M. Hanafy AU - Guma Ali AU - Fawaz Alzahrani AU - Atef Fathy Ahmed PY - 2025 JO - Scientific Reports DO - 10.1038/s41598-025-30739-2 UR - https://doi.org/10.1038/s41598-025-30739-2 ER -
APA
Elwakeel, A. E., Elden, A. Z., Ahmed, S. F., Issa, S., Li, C., Ali, K. A. M., Hanafy, W. M., Ali, G., Alzahrani, F., & Ahmed, A. F. (2025). Development, performance evaluation and prediction of optimal operational conditions for a double-row sugarcane harvester using deep learning. Scientific Reports. https://doi.org/10.1038/s41598-025-30739-2
Source records
- crossref · retrieved 2026-09-25T14:18:00.121Z