YOLO-Ginseng: a detection method for ginseng fruit in natural agricultural environment
Compared to other models, YOLO-Ginseng demonstrates superior overall detection performance. During the model deployment experiments, YOLO-Ginseng successfully performs real-time detection of ginseng fruits on the Jetson Orin Nano computing device, exhibiting good detection results. The average detection speed reaches 24.9 fps. The above results verify the effectiveness and practicability of YOLO-Ginseng, which creates primary conditions for the development of intelligent ginseng fruit picking equipment.
Authors
- Hongyu Guo (ORCID: https://orcid.org/0000-0003-0487-3610)
- Zhuang Yang (ORCID: https://orcid.org/0000-0003-3886-1044)
- Chao Li (ORCID: https://orcid.org/0000-0001-6380-862X)
- Zhedong Xie
- Jiazhuo Jiang
- Zhen Zhang (ORCID: https://orcid.org/0000-0002-0647-4253)
Institutions
- Jilin Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2024-11-20
- DOI
- https://doi.org/10.3389/fpls.2024.1422460
- Citations
- 7
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 4.20
Funders
- People's Government of Jilin Province