YOLOv5 achieved 13.3% mean average precision at mAP 0.5:0.95.

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

Outcome: mAP 0.5:0.95e0
Value: 13.3%e0

Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Verbatim

e0
“13.3% (mAP 0.5:0.95)”
✓ located verbatim in the source · abstract, characters 727–747

Title

Design and Development of a Leaf Blight Detection System Using Image Processing with Intrusion Notification via SMS

Gina L. Hanopol; Jennifer C. Dela Cruz 2023 IEEE 14th Control and System Graduate Research Colloquium (ICSGRC) 2023. doi:10.1109/icsgrc57744.2023.10215447

Other claims from this paper (3)

Method / resource YOLOv5 detected leaf blight with mean average precision of 38.80% at mAP 0.5.
Method / resource YOLOv5 precision was 56%.
Method / resource YOLOv5 recall was 37.90%.

Record rev-e0723302c334fb96f7328b65f01c08c2d20ab8e56a6635598162850b7ce3ed67 · schema claims-v0.9 · position 2 in the model’s answer