Claim · model-written summary
YOLOv11s was selected among four models for F1-score, fewest false negatives and real-time performance.
- Taxon
- pear orchardse1
- Outcome
- F1-score, lowest false negatives (FN) count, and real-time performancee0
- Comparator
- four evaluated YOLO modelse0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingDirectionValueQualifier
Verbatim
e0“Among the four evaluated YOLO models, YOLOv11s was selected based on its F1-score, lowest false negatives (FN) count, and real-time performance.”
e1“horizontal trellis pear orchards”
t0“Orchards”
Title
LiDAR–Camera Fusion for 3D Fruit Counting and Density Mapping in Horizontal Trellis Orchards
Jaehwan Lee; Meguna Ohata; Hiromichi Itoh; et al. Journal of Robotics and Mechatronics 2026. doi:10.20965/jrm.2026.p0449
Other claims from this paper (3)
- Method / resource Field validation found fruit-counting accuracy of 96.2%.
- Method / resource Spatial density estimation had mean absolute error of 0.64 fruits/m 2 .
- Method / resource The system identified yield variation among orchard regions.