Towards smart farming: a real-time diagnosis system for strawberry foliar diseases using deep learning

The proposed system is trained on two publicly available datasets, PlantDoc and PlantVillage. It attains a precision of 91.10% and a recall of 88.50%, while maintaining a real-time processing speed of 76.50 frames per second (fps). Experimental field inspection of strawberry studies demonstrates that the proposed model significantly outperforms existing approaches in accuracy and efficiency.