DINOV2-FCS: a model for fruit leaf disease classification and severity prediction
The results demonstrate that the model exhibits superior performance compared to other state-of-the-art models and that the model has strong generalization capabilities. This study provides a new method for leaf disease classification and leaf disease severity prediction for a variety of fruits. Code is available at https://github.com/BaiChunhui2001/DINOV2-FCS.
Authors
- Lutao Gao (ORCID: https://orcid.org/0009-0002-1097-619X)
- Lilian Zhang (ORCID: https://orcid.org/0000-0002-7823-5091)
- Peng Lin (ORCID: https://orcid.org/0000-0002-7589-3160)
- Peishan Li (ORCID: https://orcid.org/0000-0003-4138-4437)
- 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
- 2024-12-06
- DOI
- https://doi.org/10.3389/fpls.2024.1475282
- Citations
- 2
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.20