Plant Disease Detection Using Convolutional Neural Networks (CNNs)

Plant disease detection is crucial for ensuring agri-cultural productivity and food security. However, accurately identifying diseases across various crops remains a challenge, particularly in resource-constrained regions. This study addresses this issue by developing a single convolutional neural network (CNN) model capable of identifying diseases across multiple crop types. Using a comprehensive dataset containing labelled images of healthy and diseased leaves from various crops: including apples, potatoes, and bell peppers, the model was trained to recognize both the crop type and the specific disease.