A Review of Convolutional Neural Network-based Approaches for Disease Detection in Plants

Around 60.3% of land in India is used for agricultural purposes and the whole population depends on agriculture. That’s why crop yield is very crucial to get high agricultural output. The economical loss will be very high if the agricultural output is low. So, that’s why the diagnosis of disease in plants is very important. And the detection should be in the early stage not in a later stage. Using Deep Learning (DL) i.e. a branch of Artificial Intelligence (AI), a farmer can detect plant diseases very easily. In Deep Learning(DL), Convolutional Neural Networks (CNNs) are a cutting-edge method for image classification tasks. And Plant Disease Detection is an image classification task in which image is given as input and a class of plant disease is obtained as an output. This research study reviews the CNN-based approaches that are used to detect various diseases in plants.