Explainable Lightweight Deep Learning for Plant Leaf Disease Detection Using MobileNet and Grad-CAM

This research proposes an explainable lightweight deep learning framework for plant leaf disease detection using MobileNetV2 and Grad-CAM. The proposed approach achieves high classification performance while reducing computational complexity, making it suitable for mobile and resource-limited agricultural applications. MobileNetV2 is compared with EfficientNetB0 and ResNet50 based on accuracy, precision, recall, F1-score, model parameters, and inference time. Grad-CAM is integrated to provide visual explanations by highlighting disease-relevant regions of leaf images, improving model transparency and reliability.