PotatoGuardNet: a refined deep learning framework for potato leaf disease detection

Key Points

• The proposed framework achieves accurate localization and classification of potato leaf diseases, enhancing detection efficiency.
• Comparative analyses confirm the reliability of PotatoGuardNet against recent state-of-the-art approaches, showing significant improvements.
• Experiments demonstrate the ability to capture disease-specific visual patterns, facilitating early and accurate diagnosis in crops.
• Deployment in automated agricultural disease monitoring systems appears feasible, supporting timely responses to outbreaks.

Abstract