A comprehensive analysis of YOLO architectures for tomato leaf disease identification
Abstract Tomato leaf disease detection is critical in precision agriculture for safeguarding crop health and optimizing yields. This study compares the latest YOLO architectures, including YOLOv8, YOLOv9, YOLOv10, YOLOv11, and YOLOv12, using the Tomato-Village dataset, which contains 14,368 images a...
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| Main Authors: | Leo Thomas Ramos, Angel D. Sappa |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-07-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-11064-0 |
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