A Comparative Study of Disease Detection in Potato Plants Using Machine Learning and Deep Learning Methods

For the sustainability of human life, potato crop agriculture development is crucial. Potato plant disease, despite the hoopla, does substantial damage to potatoes. Early blight, late blight, and other diseases can spread in potato plants and display symptoms on leaves. If these epidemics are recognized early and preventative measures are followed, cultivators will not suffer significant financial losses. During the comparison analysis paper, the intended model was able to accurately determine and detect diseases in potato leaf stands using CNN which includes ResNet algorithm and UNet model which comes under deep learning methods. We tried both machine learning (SVM) and deep learning model (ResNet, UNet). We found best result from ResNet algorithm over other models with an accuracy of 99.6%.