Cherry-Net: real-time segmentation algorithm of cherry maturity based on improved PIDNet
This study presents a lightweight, accurate, and efficient solution for cherry maturity recognition and contour detection in robotic harvesting. The proposed approach enhances robustness under challenging agricultural conditions and shows strong potential for deployment in intelligent harvesting systems, contributing to the advancement of precision agriculture technologies.
Authors
- Jie Cui (ORCID: https://orcid.org/0000-0001-9391-6744)
- Lutao Gao (ORCID: https://orcid.org/0009-0002-1097-619X)
- Lilian Zhang (ORCID: https://orcid.org/0000-0002-7823-5091)
- Chunhui Bai
- Linnan Yang (ORCID: https://orcid.org/0009-0005-2058-0895)
Institutions
- Yunnan Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-09-03
- DOI
- https://doi.org/10.3389/fpls.2025.1607205
- Citations
- 3
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 5.25