Claim · model-written summary
YOLOv8nGP improved soybean recognition recall by 1.1% over YOLOv8n.
- Taxon
- soybean
Glycine maxt0 - Outcome
- Recall (R)e0
- Direction
- improvese0
- Value
- 1.1%e0
- Comparator
- original YOLOv8ne0
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentSettingQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.

Verbatim
e0“Compared with the original YOLOv8n, the YOLOv8nGP improves the Precision (P), Recall (R), and F1 metrics by 1.1% each”
t0“Soybean”
Title
Weed Recognition at Soybean Seedling Stage Based on YOLOV8nGP + NExG Algorithm
Tao Sun; Longfei Cui; Lixuan Zong; et al. Agronomy 2024. doi:10.3390/agronomy14040657
Other claims from this paper (5)
- Method / resource YOLOv8nGP improved soybean recognition precision by 1.1% over YOLOv8n.
- Method / resource YOLOv8nGP improved soybean recognition F1 by 1.1% over YOLOv8n.
- Method / resource YOLOv8nGP reduced model size by 3.6 mb.
- Method / resource YOLOv8nGP inference time was 2.2 ms.
- Method / resource The segmentation method reduced dependence on weed dataset diversity.