The online tomato detection speed reached 6 /s.

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

Taxon: TomatoSolanum lycopersicumt0
Outcome: online detection speede0
Value: 6 /se0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

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

*Solanum lycopersicum* · TaxonKod B · CC BY-SA 4.0 · Wikimedia Commons ↗

Verbatim

e0
“the online detection speed reaches 6 /s”
✓ located verbatim in the source · abstract, characters 906–945

t0
“Tomato”
✓ located verbatim in the source · title, characters 0–6

Title

Tomato grading based on Machine vision D-S multi-feature fusion algorithm

Yanzhi Bi; Chao Zhang; Peisi Zhong; et al. International Conference on Algorithms Software Engineering and Network Security 2024. doi:10.1145/3677182.3677220

Other claims from this paper (3)

Method / resource The improved edge detection method better extracted tomato edge features.
Method / resource Average tomato quality classification accuracy was 91%.
Method / resource Multi-feature fusion classification was relatively higher in speed and accuracy than single-feature classification.

Record rev-16fca3c8cb3d554c2539f7f55f143e236630eb2bd3a816a4cf938b414165ec61 · schema claims-v0.9 · position 2 in the model’s answer