Claim · model-written summary
The improved model increased mAP@0.5-0.95 for small tassels by 5.3 over the original model.
Zea maysNot reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Maize tassels detection is essential for future agronomic management in maize planting and breeding”
e2“The mAP@0.5, mAP@0.5-0.95, mAP@0.5-0.95(area=small), and mAP@0.5-0.95(area=medium) average increased by 1.5, 1.8, 5.3, and 1.7%, respectively than the original model”
Title
Detection of maize tassels for UAV remote sensing image with an improved YOLOX Model
Chao-yu SONG; Fan ZHANG; Jian-sheng LI; et al. Journal of Integrative Agriculture 2022. doi:10.1016/j.jia.2022.09.021
Other claims from this paper (4)
- Method / resource The SEYOLOX-tiny model detects maize tassels with a mean average precision (mAP@0.5) of 95.0%.
- Method / resource The improved model increased mAP@0.5 by 1.5 over the original model for maize tassel detection.
- Method / resource The improved model increased mAP@0.5-0.95 by 1.8 over the original model for maize tassel detection.
- Method / resource The improved model increased mAP@0.5-0.95 for medium tassels by 1.7 over the original model.