Plant Disease Detection Using CNN

Abstract

Early Disease Detection and pets are important for better yield and quality of crops. With Reduction in Quality of the agricultural Product, Disease Plant can lead to the huge Economic Losses to the Individual farmers. In country like India whose major Population is involved in Agriculture It is very important to find the disease at early stages. Faster and precise prediction of plant disease could help reducing the losses. With the Significant advancement and developments in Deep learning have given the Opportunity to improve the performance and accuracy of detection of object and recognition system. This Paper, focuses on finding the plant diseases and reducing the economic losses. We have proposed the deep leaning based approach for image recognition. We have examined the three main Architecture of the Neural Network: Faster Region-based Convolution Neural Network (Faster R-CNN), Region-based Fully CNN(R-CNN) and Single shot Multibook Detector (SSD). System Proposed in the paper can Detect the different types of disease efficiently and have the ability to deal with complex scenarios. Validation result show the accuracy of 94.6% which depicts the feasibility of Convolution Neural Network and present the path for AI based Deep Learning Solution to this Complex Problem.