Qureshi, RehaalKhan, Ehtesham [22CO18]Siddiqui, Amil [22CO59]Karche, Shahid [23DCO02]Parkar, Uzair [21CO33]2026-08-202026-08-202026-06http://aiktc.ndl.gov.in/handle/123456789/4562This project focuses on developing a Plant Disease Detection System using Convolutional Neural Networks (CNN) which a type of deep learning model widely used in image classification tasks. The system can accurately identify and classify various plant diseases from leaf images. The model is trained on a large dataset containing images of healthy and diseased leaves of multiple crops such as apple, tomato, potato, corn, grape, and more. It can detect up to 30 different plant diseases with high accuracy. By using image processing and deep learning techniques, this model helps farmers and agriculturists quickly identify plant diseases and take preventive measures, thereby reducing crop loss and improving productivity. The trained CNN model is integrated into a simple web interface (or mobilefriendly app) where users can upload a leaf image to get an instant prediction of the disease along with its name and confidence score.en-USProject Report