CONVOLUTION NEURAL NETWORK FOR LEAF DISEASE DETECTION

Abstract

Plants are the major source of food for all kinds of living beings. With the increase in population, it is now more important to keep this supply continue. To cop-up with such high demand, it is very important keep the plants healthy from various kinds of diseases. The detection of disease is sometimes very difficult for even experienced farmers. In the agriculture sector plant leaf diseases and destructive insects are a major challenge. To reduce economical losses need to develop an early treatment technique which should faster and accurate in prediction of leaf disease in crops. Modern advanced developments in artificial intelligent using machine learning have allowed researchers to extremely improve the performance and accuracy of object detection and recognition systems. In this paper, proposed a deep-learning-based approach to detect leaf diseases in plants using images of plant leaves. Goal is to find and develop the more suitable system for our task. To develop this system, used Convolutional Neural Network [CNN] for image processing. The proposed system can effectively identified different types of diseases with the ability to deal with complex scenarios from a plant’s area.