Detection of diseased plants by using convolutional neural network

Abstract

Agricultural takes a major percentage in a country’s economic growth. Crop production plays an essential role in agriculture. Countries’ economical growth rate is reduced due to less crop production. Foods are essential for every living being, since we need proper food for survival. Hence, it is essential for every farmer to cultivate a healthy plant to increase the crop production. However, in nature, every plant can get attacked by some sort of disease but the level of damage occurred to the crops are different for every plant. If a fully matured plant get affected by a simple disease, it will not affect the full plant but if a small plant gets affected by the same disease, it causes severe damage to the plant, as we cannot manually monitor the plants and cannot detect the disease occurring in the plants everyday. Huge manpower is needed to monitor every plant in the farm so it needs time for monitoring every crop in the field. In this paper, image recognition using conventional neural network (CNN) has been proposed to reduce the time complexity and manpower requirement. The proposed algorithm accurately detects the type of diseases that occurs in the plants.