Method / resourcemodel-written summary

The method reached 93.6% wheat detection accuracy under different light intensities.

A claim from Field Wheat Ears Count Based on YOLOv3 · 2019

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

The method reached 93.6% wheat detection accuracy under different light intensities.

Outcome
detection accuracye0
Value
93.6%e0
Qualifier
under different light intensitiese0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirection

Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Triticum aestivum
Triticum aestivum · TaxonRasbak · CC BY-SA 3.0 · Wikimedia Commons ↗

Verbatim

e0

“After several experiments under different light intensities, the detection accuracy of the method reached 93.6%”

✓ located verbatim in the source · abstract, characters 979–1090
t0

“Field Wheat Ears Count Based on YOLOv3”

✓ located verbatim in the source · title, characters 0–38

Title

Field Wheat Ears Count Based on YOLOv3

Yvhang Yang; Xi Huang; Liangben Cao; et al. 2019 International Conference on Artificial Intelligence and Advanced Manufacturing (AIAM) 2019. doi:10.1109/aiam48774.2019.00094

Other claims from this paper (1)

Record rev-b44e896390a193ba80f639c70147f02c468c83aee7bb6f18e603506ad636ece3 · schema claims-v0.9 · position 1 in the model’s answer