AHG-YOLO: multi-category detection for occluded pear fruits in complex orchard scenes
The improved model demonstrates enhanced suitability for deployment on pear-harvesting embedded devices, providing technical support for the path planning of fruit-picking robotic arms.
Authors
- Na Ma
- Chenfei Li (ORCID: https://orcid.org/0000-0001-9497-4620)
- Haiyan Song (ORCID: https://orcid.org/0000-0003-2155-8110)
- Yile Sun (ORCID: https://orcid.org/0000-0003-2889-6155)
- Zonglin Liu (ORCID: https://orcid.org/0009-0009-6410-2798)
Institutions
- Shanxi Agricultural University (CN)
- China Academy Of Machinery Science & Technology (China) (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-05-23
- DOI
- https://doi.org/10.3389/fpls.2025.1580325
- Citations
- 8
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 14.00