Analysis of Deep Learning Models for Potato Leaf Disease Classification and Prediction

Plant diseases reduce yields, directly affecting domestic and global food production systems. Using image classification and early prediction of plant diseases can help us to manage yield production properly. This study evaluated the deep learning models VGG19 and ResNet50 for potato leaf disease classification and prediction. The performance of deep learning models VGG19 and Resnet50 is recorded based on performance metrics such as confusion matrix, precision, recall, accuracy, f1-score, and ROC/AUC. The models VGG19 and Resnet50 achieved the highest accuracy at 93% and 92.58%, respectively.