Constructive Application For Hygiene Sustainability In Plants

Abstract

Agriculture is the most predominant part of the Indian Economy. Tomato plays a vital role in the Indian market with a huge yielding rate in large quantities. To ensure that diseases are harmful to the crops, it is very much important to supervise it with particular care. There are legion types of tomato disease identification methods to supervise the plant leaves. This paper makes use of current trending technology deep convolutional neural network, to make use of identifying the diseases. The main agenda of the proposed work is to predict the presence of diseases in plant leaves and also to detect those diseases in the initial stages itself using the simplest approach with less computational resources. This proposed work deals with tomato plant leaf and disease as a Bacterial leaf spot. Deep learning-based neural network architecture namely VGG16 is well suitable for image processing to extract the features from an input image and relate it to the different classes. The model consists of convolutional layers followed by pooling layers

Keywords: bacterial, crops, convolutional, features, neural, tomato, leaf