Identification of Pathological Disease in Plants using Deep Neural Networks - Powered by Intel® Distribution of OpenVINO™ Toolkit

Abstract

This paper deals with an algorithm for the easy identification or classification of pathological diseases in plant species via a mobile or web application. The entire system is an intelligent framework that enables users to identify a pathological disease via a deep learning and computer vision based smart system – A user merely needs to open the app, click a picture, and view the result. Input for the system can be either an image or live video feed of the plant species, and the result is in the form of a bounding box with the name of the identified pathological disease and the accuracy of the identification. Once the identification is accurately done the user can get more insights into the cause of the disease and how to do a proper medication.For this experimental research purpose, we are targeting five pathological diseases: Blister Blight in Tea, Citrus Canker, Early Blight, Late Blight, Powdery Mildew in Cucurbitaceae. This paper illustrates how the solution is built using deep learning and computer vision algorithms powered by the Intel® Distribution of Open VINO™ toolkit Model Optimizer.