A Super Resolution CNN based Model for Crop Disease Detection

Abstract

The major contribution to Indian economy comes from agriculture which stands as the backbone and also it is the livelihood of many farmers. But now-a-days the crops are being infected by multiple diseases and causing widespread of the disease which in turn damages the entire crop fields if they are not noticed in prior. Crops get diseased by fungi, virus and bacteria and also by worms and insects that attack the crops. These crop diseases should be diagnosed with the help of emerging technologies like DL (Deep Learning) which provide plenty of techniques for disease detection. The proposed model which uses a Super Resolution Convolutional Neural Network (SRCNN) to improve the quality of the crop leaf images and also a CNN which acts as a classifier that helps to detect the crop disease. When the model is trained with SRCNN it improves the performance and illness of crops is also identified in an unerring way.