Contagion Classification using Deep Learning Approach

Potatoes are a major crop globally, but diseases can seriously harm their growth and quality. Recently, there's been a lot of interest in using machine learning to identify potato diseases from pictures. In this study, we've developed a way to automatically classify potato diseases using deep learning methods. By training a model with CNN and SVM algorithms on a dataset of potato disease images, we achieved an accuracy rate of 93.95%. This shows that deep learning is effective in identifying potato diseases. Our method could be a big help to farmers and researchers, making it faster and easier to spot and deal with potato diseases, which could lead to better crop yield and quality.