Claim · model-written summary
MobileNetV2 and DenseNet121 achieved 96.25% accuracy in chili pepper disease classification.
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
t0“chili pepper disease detection”
e4“MobileNetV2 and DenseNet121 achieved 96.25% accuracy”
Title
Deep learning enables precision agriculture for sustainable chili pepper disease detection in Benin
Mireille Gloria Founmilayo Odounfa; Castro Gbêmêmali Hounmenou; Valère Kolawolé Salako; et al. Discover Artificial Intelligence 2025. doi:10.1007/s44163-025-00583-4
Other claims from this paper (4)
- Method / resource YOLOv8 outperformed other models in detecting and localizing chili pepper leaf diseases in real time.
- Method / resource YOLOv8 achieved a mean Average Precision (mAP@0.5) of 0.995 for chili pepper disease detection.
- Method / resource YOLOv8 achieved a mAP@0.5–0.95 of 0.941 for chili pepper disease detection.
- Method / resource YOLOv8 precision and recall exceeded 99%.