Claim · model-written summary
HMA-YOLO has a model size of 3.1 MB.
- Taxon
- corn
Zea mays subsp. mayse0 - Outcome
- model sizee5
- Value
- 3.1 MBe5
Not reportedMaterialGeneCompoundOrgan / stageInteractorInteractor roleSecond interactorSecond interactor roleTreatmentComparatorSettingDirectionQualifier
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“accurately detect corn trumpets”
e5“with only a model size of 3.1 MB”
Title
Chengxiang Zhang; Wenqiang Li; Lili Wu; et al. Frontiers in Plant Science 2026. doi:10.3389/fpls.2026.1785800
Other claims from this paper (7)
- Method / resource HMA-YOLO achieves a mAP@0.5 of 91.5% for detecting corn trumpets.
- Method / resource HMA-YOLO achieves a precision of 89.8% for detecting corn trumpets.
- Method / resource HMA-YOLO achieves a recall of 83.7% for detecting corn trumpets.
- Method / resource HMA-YOLO operates at 128 FPS.
- Method / resource HMA-YOLO has a parameter count of 1.407M.
- Method / resource HMA-YOLO outperforms mainstream object detectors in corn trumpet detection.
- Observation HMA-YOLO was successfully deployed on the NVIDIA Jetson Xavier NX embedded platform and achieves real-time and efficient detection.