Paper Title
Study an Image Processing based Approach to Identification of Banana Plant Disease using DIY Built F450 Drone

Abstract
In this research paper is an image processing-based approach is being proposed and used for banana plant disease detection and locating using Aruco Marker ID tags and a DIY-Built F450 Drone at very low cost. Author tests our results on three diseases which effect on banana crops; they are: Cordana, Pestalotiopsis and Sigatoka. The proposed approach is image processing based and is much supported Convolutional Neural Network (CNN) adopting AlexNet Architecture. The approach consists of 6 main phases; capturing images of plants with their individual Aruco Tag ID to Google Drive database from drone, data pre-processing, images are segmented using RGB to HSI conversion, applying mask to K-means clustering on the images, extracting feature from data and training Neural Network Model. Keywords - Neural Network, Convolutional Neural Network, Plant Disease, Image Processing