Method / resourcemodel-written summary

YOLOv5 precision was 56%.

A claim from Design and Development of a Leaf Blight Detection System Using Image Processing with Intrusion Notification via SMS · 2023

Method / resourceobservedoriginal resultmeasured

Claim · model-written summary

YOLOv5 precision was 56%.

Outcome
precisione0
Value
56%e0

Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

Verbatim

e0

“with a precision of 56%”

✓ located verbatim in the source · abstract, characters 749–772

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)

Record rev-2e482a42e564c156b7e58d8159bdb439e08b0d913424aa2045e412335efd6db0 · schema claims-v0.9 · position 3 in the model’s answer