LDL-MobileNetV3S: an enhanced lightweight MobileNetV3-small model for potato leaf disease diagnosis through multi-module fusion
The proposed LDL-MobileNetV3S model demonstrates superior performance and efficiency compared to several existing lightweight models. This study provides a cost-effective and high-accuracy solution for potato leaf disease diagnosis, which is particularly suitable for deployment on intelligent diagnostic devices operating in resource-limited field environments.
Authors
- Honghui Li (ORCID: https://orcid.org/0009-0003-3436-7150)
- Xiaofei Yang (ORCID: https://orcid.org/0000-0002-5118-7755)
- Jinyan Zhang (ORCID: https://orcid.org/0000-0001-6207-1507)
- Buyu Wang (ORCID: https://orcid.org/0000-0002-5002-1219)
- Xueliang Fu (ORCID: https://orcid.org/0009-0000-1882-409X)
Institutions
- Inner Mongolia Agricultural University (CN)
- Inner Mongolia Academy of Agricultural & Animal Husbandry Sciences (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-10-22
- DOI
- https://doi.org/10.3389/fpls.2025.1656731
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- Natural Science Foundation of Inner Mongolia