Enhanced-RICAP: a novel data augmentation strategy for improved deep learning-based plant disease identification and mobile diagnosis
To bridge the gap between research and practical application, the ResNet18+Enhanced-RICAP model was deployed in PlantDisease, a mobile application that enables real-time disease identification and management recommendations. This approach supports sustainable agriculture and strengthens food security by providing farmers with accessible and reliable diagnostic tools.
Authors
- Mohamed Meyer Kana Kone
- Linjing Wei
- Solomon Boamah (ORCID: https://orcid.org/0000-0003-0243-7276)
- Yue Li (ORCID: https://orcid.org/0000-0002-1679-2941)
- Mamadou Bailo Diallo
- Yuhong Gao (ORCID: https://orcid.org/0009-0004-7709-1796)
- Okafor Sylevester Chukwuka
- Gelebo Rocho
Institutions
- Jiangxi University of Water Resources and Electric Power (CN)
- Nanchang University (CN)
- Gansu Agricultural University (CN)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-09-24
- DOI
- https://doi.org/10.3389/fpls.2025.1646611
- Citations
- 3
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 5.25