A novel transformer using dynamic range-enhanced discrete cosine transform for detecting bean leaf diseases
These findings indicate that enhancing feature extraction through DRE-DCT significantly improves disease classification performance. The proposed method offers an efficient solution for early disease detection in agriculture, contributing to improved disease management strategies and supporting food security initiatives.
Authors
- İbrahim Furkan İnce (ORCID: https://orcid.org/0000-0003-1570-875X)
- Faruk Bulut (ORCID: https://orcid.org/0000-0003-2960-8725)
- Shaira Osmani
- Harisu Abdullahi Shehu (ORCID: https://orcid.org/0000-0002-9689-3290)
Institutions
- University of Essex (GB)
- International Center for Research on Women (US)
- Victoria University of Wellington (NZ)
- Istinye University (TR)
- Istanbul Commerce University (TR)
- Istanbul University (TR)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-08-29
- DOI
- https://doi.org/10.3389/fpls.2025.1624373
- Citations
- 1
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 1.75
Funders
- University of Essex