A multimodal dual-branch attention-centric YOLOv12 framework for real-time integrated pest and weed detection from UAV imagery in precision agriculture
- DOI
- 10.1038/s41598-026-59582-9
- Published
- 2026-06-30
- 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/s41598-026-59582-9,
title = {A multimodal dual-branch attention-centric YOLOv12 framework for real-time integrated pest and weed detection from UAV imagery in precision agriculture},
author = {Porkodi Karuvelampalayam Prabhakaran and Geetha Anbazhagan and Preethi Srinivasan and Thenkaraimuthu Mariprasath and Chenniyappa Goundar Janarathanam Vignesh and Mustafa Abdullah and Mykhailo Panchyk},
year = {2026},
journal = {Scientific Reports},
doi = {10.1038/s41598-026-59582-9},
url = {https://doi.org/10.1038/s41598-026-59582-9}
}RIS
TY - JOUR TI - A multimodal dual-branch attention-centric YOLOv12 framework for real-time integrated pest and weed detection from UAV imagery in precision agriculture AU - Porkodi Karuvelampalayam Prabhakaran AU - Geetha Anbazhagan AU - Preethi Srinivasan AU - Thenkaraimuthu Mariprasath AU - Chenniyappa Goundar Janarathanam Vignesh AU - Mustafa Abdullah AU - Mykhailo Panchyk PY - 2026 JO - Scientific Reports DO - 10.1038/s41598-026-59582-9 UR - https://doi.org/10.1038/s41598-026-59582-9 ER -
APA
Prabhakaran, P. K., Anbazhagan, G., Srinivasan, P., Mariprasath, T., Vignesh, C. G. J., Abdullah, M., & Panchyk, M. (2026). A multimodal dual-branch attention-centric YOLOv12 framework for real-time integrated pest and weed detection from UAV imagery in precision agriculture. Scientific Reports. https://doi.org/10.1038/s41598-026-59582-9
Source records
- crossref · retrieved 2026-09-25T12:40:21.094Z