Plant Disease Detection Mobile Application Development using Deep Learning

Abstract

A large portion of crops are lost to plant diseases each year worldwide. In this study, a mobile application for detecting and classifying plant disease using deep learning object detection model was developed. The proposed mobile application utilizes Faster R-CNN object detector with Inception-v2 backbone network to achieve robust and efficient detection. Experiments on grape disease images demonstrated that the proposed application is able to achieve an accuracy of 97.9% while running solely on a smartphone without connecting to a server. The proposed mobile application can serve as an aid to farmers and crop growers who have little or no knowledge about plant diseases for early disease detection and control and therefore can reduce losses and prevent further spreading of the disease.