Claim · model-written summary
In field tests, Seedling-YOLO reached an actual detection precision of 93% for broccoli seedlings.
- Taxon
- broccoli
Brassica oleracea var. italicat0 - Outcome
- actual detection precisione5
- Value
- 93%e5
- Setting
- field testse6
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
t0“Field Broccoli Seedling Transplanting Quality”
e5“It achieved an actual detection precision of 93% and a detection efficiency of 180 plants/min”
e6“In field tests conducted with double-row vegetable ridges at a plant spacing of 0.4 m and robot speed of 0.6 m/s”
Title
Tengfei Zhang; Jinhao Zhou; Wei Liu; et al. Agronomy 2024. doi:10.3390/agronomy14050931
Other claims from this paper (6)
- Method / resource Seedling-YOLO outperforms YOLOv4-tiny, YOLOv5s, YOLOv7-tiny and YOLOv7 in speed and precision for broccoli planting-quality detection.
- Method / resource Seedling-YOLO reached an Average Precision of 94.2% for exposed seedlings.
- Method / resource Seedling-YOLO reached an Average Precision of 92.2% for missed hills.
- Method / resource Seedling-YOLO achieved a mean Average Precision of 0.5 (mAP@0.5) of 94.3%.
- Method / resource Seedling-YOLO ran at a frame rate of 29.7 frames per second.
- Method / resource In field tests, Seedling-YOLO reached a detection efficiency of 180 plants/min.