research on soyabean leaves

This project focuses on developing an intelligent system capable of detecting and classifying diseases in plant leaves using image processing and deep learning techniques. Leveraging Convolutional Neural Networks (CNNs) and transfer learning, the system analyzes leaf images to identify signs of infection with high accuracy. It supports smart agriculture by enabling early disease detection, reducing crop loss, and providing actionable insights to farmers. The project uses datasets such as PlantVillage and integrates frameworks like TensorFlow, Keras, and PyTorch. The model can be deployed as a web or mobile application, offering a real-time solution for plant health monitoring in agricultural environments.