Intelligent smart sensing with ResNet-PCA and hybrid ML–DNN for sustainable and accurate plant disease detection
The obtained results confirm the hybrid ML+DNN paradigm as a safe, transparent, scalable disease recognition framework when applied to plant diseases. Providing opportunities for timely and accurate disease detection, the proposed framework can help with precision agriculture, where pesticide use can be reduced, consequently, and a significant contribution to sustainable farming can be achieved.
Authors
- Shtwai Alsubai (ORCID: https://orcid.org/0000-0002-6584-7400)
- Thippa Reddy Gadekallu
- Ahmad Almadhor (ORCID: https://orcid.org/0000-0002-8665-1669)
- Abdullah Al Hejaili (ORCID: https://orcid.org/0000-0002-8388-4723)
Institutions
- Lovely Professional University (IN)
- Zhejiang A & F University (CN)
- Prince Sattam Bin Abdulaziz University (SA)
- Jouf University (SA)
- Jiaxing University (CN)
- University of Tabuk (SA)
Publication Details
- Journal
- Frontiers in Plant Science
- Published
- 2025-11-06
- DOI
- https://doi.org/10.3389/fpls.2025.1691415
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Prince Sattam bin Abdulaziz University