Flower Disease Detection Using CNN

Abstract

The continuous change in the environment is harmful to the crops and leads farmers toward debt and suicide. Most of the science students intend to provide solutions to the farmers who are involved in major crop production neglecting small-scale farmers. This project aims to develop a framework for the classification of diseases that can be seen in marigold flowers. The addition of global mobile phone utilization and recent enhancement in computer vision made possible by deep learning has floored the way for disease detection. 97% accuracy is achieved by the model using a convolutional neural network in conjunction with a fully connected layer. This project summarizes the need for an application to provide a background about a disease, its symptoms, the different disease aetiologia, and its treatment.