Plant Disease Classification using Deep Learning

Abstract

In a country like Bangladesh plant disease is a common factor. The timely and accurate diagnosis of plant disease plays a very important role in preventing the loss of productivity and loss of reduce quality of agricultural product. Till now many Machine learning (ML) models have been employed for the detection and classification of plant disease. For advancement Deep learning (DL) has also employed in this research area and it has shown a vital impact in disease detection accuracy. In this paper we classified ‘15’ species of crops from 20,069 images. The dataset have been taken from plant village. We have considered here Support Vector machine which is a supervised learning algorithm for classification and regression.We also used Sequential Model for detection. We have used Train-Test-split model to train the dataset and we achieved 92.5% accuracy.