Plant Disease Detection
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Published:2022-05-31
Issue:5
Volume:10
Page:4538-4542
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ISSN:2321-9653
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Container-title:International Journal for Research in Applied Science and Engineering Technology
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language:
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Short-container-title:IJRASET
Author:
Manvi Goutami G,K N Gayana,Sree G Ramya,Divyanjali K,Patil Dr Kirankumari
Abstract
Abstract: Plant growth is major requirement for framers, as it creates a path for their living, plants getting affected and their growth is related hand in hand. Framers strive to cultivate healthy crops; in spite of it plants getting affected are the major cause of crop failure. Plant disease is now the risk factor not only for framers but also to customers, environment and global economy. Immoderate pesticide usage is the cause for major health issues in plants. Plant disease detection using image processing can be the best way to predict and get accurate results. This project is based on deep convolutional neural networks which enhances the accuracy and training efficiency. This application will help many farmers who are uneducated to get correct information about diseases and help increase their yield. We are fostering a web application that can distinguish plant infection. The objective is to distinguish different plant infection by checking picture out. By utilizing CNN Algorithm we can identify the plant disease precisely. By the results of accuracy it shows this model is better than any traditional framing. Keywords: Plant Diseases, Deep Learning, Convolutional Neural Networks
Publisher
International Journal for Research in Applied Science and Engineering Technology (IJRASET)
Subject
General Earth and Planetary Sciences,General Environmental Science
Cited by
1 articles.
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