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This research investigates the use of the YOLOv4 algorithm for the accurate detection and identification of plant leaf diseases, utilizing the Plant Village Dataset with over fifty thousand images. The study demonstrates that YOLOv4 achieves an impressive accuracy of 99.99%, outperforming traditional methods and showcasing its effectiveness in real-time disease prediction. The findings highlight significant advancements in agricultural practices, providing valuable tools for farmers and researchers in disea

Author

Kiên Phạm

Language

EN