Plant Disease Detection Using Convolutional Neural Networks

Abstract

Detection of various plant infections is the essential task for avoiding the losses in harvest and amount of the farming product. The research of the plant infections involves the study of graphical detectable patterns visible on the plant. Wellbeing examining and infection finding on plants is extremely crucial for environmental agriculture. It is extremely tough to examine the plant disease physically. It needs enormous quantity of work, skills in the plant infections, and also need the extreme execution time. Therefore, image processing is applied for the discovery of plant diseases. This detection includes the phases like image acquisition, image pre-processing, image segmentation, feature extraction and classification. This paper discusses the techniques required used for the discovery of plant diseases utilizing the leaves images. This paper also examined some segmentation and feature extraction algorithm utilized in the plant diseased detection.