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This research presents a deep learning model utilizing Explainable AI (XAI) and transfer learning for the classification of potato leaf diseases, achieving validation and testing accuracies of 97% and 98%, respectively. The model employs Grad-CAM for interpretability, enhancing transparency in decision-making processes crucial for agricultural practices. The study addresses the challenges of timely disease identification and the need for automated detection methods in agriculture, leveraging a publicly avai
- Author
- chancewu1
- Language
- EN