Claim · model-written summary
The improved vision transformer achieved more precise detection of wheat stripe rust than previous methods.
- Taxon
- wheat
Triticum aestivume0 - Outcome
- precise detection of wheat stripe ruste0
- Comparator
- previous methodse0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Using an improved vision transformer, we achieved precise detection of wheat stripe rust compared to previous methods”
Title
An Enhanced Wheat Stripe Rust Segmentation Approach Using Vision Transformer Model
Nosheen Usman; Tauqir Ahmad; Faiza Iqbal; et al. International Journal of Computational Intelligence Systems 2025. doi:10.1007/s44196-025-00873-w
Other claims from this paper (4)
- Method / resource The proposed vision transformer detected wheat stripe rust with 98% accuracy.
- Method / resource The proposed hybrid approach detected wheat stripe rust with 97.9% accuracy.
- Method / resource The ViT-Base/16 model achieved an accuracy of about 98% on the same datasets.
- Method / resource The transformer model achieved an accuracy of about 95% on the same datasets.