Method / resourcemodel-written summary

ShuffleNet detected wheat leaf rust with 94.59% accuracy.

A claim from Small CNN Architectures for Wheat Leaf Rust Detection: A MobileNetV2 and ShuffleNet Approach with SVM · 2024

Method / resourceobservedoriginal resultpositivemeasured

Claim · model-written summary

ShuffleNet detected wheat leaf rust with 94.59% accuracy.

Outcome
Acc.e0
Value
94.59%e0

Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier

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

“ShuffleNet attained an Acc. of 94.59%”

✓ located verbatim in the source · abstract, characters 591–628
t0

“Wheat Leaf Rust Detection”

✓ located verbatim in the source · title, characters 28–53

Title

Small CNN Architectures for Wheat Leaf Rust Detection: A MobileNetV2 and ShuffleNet Approach with SVM

Chilaka Rao; Santi Kumari Behera; Prabira Kumar Sethy 2024 8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC) 2024. doi:10.1109/i-smac61858.2024.10714622

Other claims from this paper (16)

Record rev-d801e2e238cdac286a9142679ab4c5c6ed22d7996633dcc18ae4d8bcc305a2ba · schema claims-v0.9 · position 5 in the model’s answer