Sustainable deep vision systems for date fruit quality assessment using attention-enhanced deep learning models
These results underscore the effectiveness of the proposed method compared to widely used architecture, providing a robust and practical solution for automating fruit classification and quality control in the food industry.
Authors
- Esraa Hassan (ORCID: https://orcid.org/0000-0002-1021-717X)
- Nora El-Rashidy (ORCID: https://orcid.org/0000-0001-8177-9439)
- Tarek Abd El‐Hafeez (ORCID: https://orcid.org/0000-0003-1785-1058)
- Mahmoud Y. Shams (ORCID: https://orcid.org/0000-0003-3021-5902)
- Sarah Abu Ghazalah
Institutions
- Kafrelsheikh University (EG)
- Deraya University
- King Khalid University (SA)
- Minia University (EG)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-06-30
- DOI
- https://doi.org/10.3389/fpls.2025.1521508
- Citations
- 30
- Primary Topic
- Date Palm Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 52.49
Funders
- King Khalid University