Claim · model-written summary
CTNet attains 91.81% accuracy on the CottonWeedID15 dataset.
Not reportedTaxonMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorDirectionQualifier
Verbatim
e0“On three normal-collected datasets (PlantVillage, CottonWeedID15, and PotatoLeafDisease) the model attains accuracies of 99.74%, 91.81%, and 99.52%, respectively”
Title
Bo Han; Heguang Sun; Wenqian Tang; et al. Artificial Intelligence in Agriculture 2026. doi:10.1016/j.aiia.2026.05.003
Other claims from this paper (7)
- Method / resource CTNet achieves 99.03% accuracy on the augmented custom lychee disease dataset.
- Method / resource CTNet attains 99.74% accuracy on the PlantVillage dataset.
- Method / resource CTNet attains 99.52% accuracy on the PotatoLeafDisease dataset.
- Method / resource CTNet reaches 97.45% accuracy on the PlantSeedling dataset.
- Method / resource CTNet reaches 99.97% accuracy on the RiceImage dataset.
- Method / resource CTNet reaches 93.08% accuracy on the SoyBeanSeed dataset.
- Method / resource CTNet consistently outperforms state-of-the-art classification methods across all benchmarks.