Advanced Plant Disease Detection Using Neural Network

Abstract

The latest generation of convolutional neural networks (CNNs) has achieved impressive results in the field of image classification. This paper is concerned with a new approach to the development of tomato plant disease recognition model, based on leaf image classification, by the use of deep convolutionalnetworks. Novel way of training and the methodology used facilitate a quick and easy system implementation in practice. The developed model is able to recognize different types of tomato plant diseases out of healthy leaves, with the ability to distinguish plant leaves from their surroundings. According to our knowledge, this method for plant disease recognition has been proposed for the first time. All essential steps required for implementing this disease recognition model are fully described throughout the project, starting from gathering images in order to create a database, assessed by agricultural experts. Neural network, was used to perform the disease detection. The experimental results on the developed model achieved detection between 85% and 95%.