Claim · model-written summary
YOLO11 trained on the dataset shows state-of-the-art performance in identifying and segmenting overlapping soybean and cotton foliage.
- Taxon
- Soybean and cotton
Gossypium hirsutum
Glycine maxe0 - Outcome
- identifying and segmenting overlapping foliagee3
- Comparator
- state-of-the-arte3
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.


Verbatim
e0“Soybean and cotton are major drivers of many countries' agricultural sectors”
e3“We validate this dataset using YOLO11, demonstrating state-of-the-art performance in accurately identifying and segmenting overlapping foliage”
Title
A Leaf-Level Dataset for Soybean-Cotton Detection and Segmentation
Thiago H. Segreto; Juliano D. Negri; Paulo H. Polegato; et al. Scientific Data 2026. doi:10.1038/s41597-026-07092-8
Other claims from this paper (3)
- Method / resource The dataset comprises 640 high-resolution field images of soybean and cotton from a commercial farm.
- Method / resource The dataset contains 7,221 annotated soybean leaves.
- Method / resource The dataset contains 5,190 annotated cotton leaves.