Potato Leaf Disease Detection Using Deep Learning Algorithm

Potato is a major crop across the world, but it is prone to a variety of illnesses that can impair productivity and quality. Early diagnosis of potato leaf diseases can assist farmers in taking the required steps to restrict the disease’s spread. I have developed a deep learning-based potato plant leaf disease detection model, namely a convolutional neural network (CNN) developed in TensorFlow Keras. We trained and validated the model using a collection of potato leaf pictures that included healthy leaves as well as leaves damaged by early and late blight. To categorize the photos into these three groups, we design a CNN model and train it with the dataset. The suggested technique yields great accuracy, confirming the deep learning approach’s efficacy in potato disease diagnosis.