Multi-stage tomato fruit recognition method based on improved YOLOv8
The reliability of YOLOv8-EA in identifying and locating multi-stage tomato fruits in complex environments demonstrates its efficacy in this regard and provides a technical foundation for the development of intelligent tomato picking devices.
Authors
- Weiheng Li (ORCID: https://orcid.org/0009-0008-8609-5739)
- Gang Li (ORCID: https://orcid.org/0000-0002-8573-1608)
- Qingyang Zhang
- Zhiguang Dai
- Songlin Wang (ORCID: https://orcid.org/0000-0003-1015-1905)
- Yanbin Li (ORCID: https://orcid.org/0000-0002-5285-8602)
- Yuanzhi Dong (ORCID: https://orcid.org/0009-0001-0668-8788)
- Yuliang Fu
Institutions
- North China University of Water Resources and Electric Power (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2024-09-05
- DOI
- https://doi.org/10.3389/fpls.2024.1447263
- Citations
- 10
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 6.00
Funders
- North China University of Water Resources and Electric Power
- National Natural Science Foundation of China
- Henan University of Science and Technology
- Henan University