Potato Leaf Disease Detection using Deep Learning

This project aims to develop a real-time potato leaf disease detection system using MobileNetV3 Small, a lightweight and efficient deep learning model optimized for mobile and web applications. The system will classify potato leaves into three categories: healthy, early blight, and late blight, ensuring accurate disease identification to assist farmers in early intervention. By leveraging advanced image processing techniques and deep learning, the model will be trained on a carefully curated dataset containing diverse disease symptoms to enhance classification accuracy.To make the system accessible and user-friendly, a mobile and web application will be developed, allowing farmers and agricultural experts to upload leaf images and receive instant disease predictions. This real-time feedback will help minimize crop damage, reduce financial losses, and improve agricultural productivity. By integrating AI-driven disease detection into farming practices, this solution promotes sustainable agriculture and contributes to global food security by mitigating the impact of plant diseases.