Malabar Nightshade Disease Detection Using Deep Learning Technique

Abstract

One of the most common vegetables as Malabar cultivates is increasing day by day, and the farmers are suffering from the Malabar disease known as scab disease on Malabar leaves. And the researcher is always trying to make a solution to protect Malabar from the disease. So that there are many papers already published and some of them also able to achieve a pretty accuracy, and it is sometime up to 85%. But, this is not the perfect solution for the suffering farmers who are facing the loss of cultivation. We are trying to solve the issues, and we also research on Malabar with 96.77% accuracy which is height accuracy. This approaches are implementing and design the model to detect and recognize Malabar disease and made this project with convolutional neural network (CNN) with respect to keras API and OpenCV, and this is a classification model of Malabar disease recognition system. We took the input as Malabar leaves with the fixed input size is 200 × 200 which defines the RGB Malabar leaves image.