ARCHIVES

Tomato plants often get different types of leaf diseases that can reduce the quality and quantity of crops. In this project, we use deep learning to identify these diseases by analyzing pictures of tomato leaves. We trained three models EfficientNet-B0, VGG16, and a custom CNN to recognize diseases like Early Blight, Late Blight, Leaf Mold, and more. We also built a hybrid model that combines the best parts of all three models to improve accuracy. Once the disease is detected, our system suggests the right pesticide to treat the plant. Our testing shows that the hybrid model gives better results than using each model separately. This project helps farmers quickly identify plant diseases and take the right actions to protect their crops. By doing this, we can improve crop health, prevent losses, and reduce the use of unnecessary pesticides