Image-Based Diagnosis of Bean Plant Health: Detection and Classification of Diseases on Beans Leaves

Bangladesh, a predominantly an agricultural country. It's common that vegetables become peaky in the time of cultivation due to some insect attack or other unavoidable activities. Accurate and early detection of plant diseases became necessary for improving crop health and ensuring better productivity. In this study, the work focused on the detection and classification of healthy and bean disease leaves using a deep learning approach based on the image classifier. The dataset contains two classes with two thousand and thirty-four thousand numbers of images. The proposed model was VGG16 which was trained and evaluated on the dataset, achieving high performance accuracy that demonstrates its robustness in distinguishing between healthy bean leaves and diseased bean leaves. Future work would be focused on further improving model performance, exploring ensemble methods and deploying the project for hand to hand uses into on-field health and disease diagnosis.