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Development of a Plant Disease Classification System using an Improved Counter Propagation Neural Network

by B.O. Ola, J.P. Oguntoye, O.O. Awodoye, M.O. Oyewole
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 20
Year of Publication: 2020
Authors: B.O. Ola, J.P. Oguntoye, O.O. Awodoye, M.O. Oyewole
10.5120/ijca2020920729

B.O. Ola, J.P. Oguntoye, O.O. Awodoye, M.O. Oyewole . Development of a Plant Disease Classification System using an Improved Counter Propagation Neural Network. International Journal of Computer Applications. 175, 20 ( Sep 2020), 19-26. DOI=10.5120/ijca2020920729

@article{ 10.5120/ijca2020920729,
author = { B.O. Ola, J.P. Oguntoye, O.O. Awodoye, M.O. Oyewole },
title = { Development of a Plant Disease Classification System using an Improved Counter Propagation Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2020 },
volume = { 175 },
number = { 20 },
month = { Sep },
year = { 2020 },
issn = { 0975-8887 },
pages = { 19-26 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume175/number20/31569-2020920729/ },
doi = { 10.5120/ijca2020920729 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:25:34.983207+05:30
%A B.O. Ola
%A J.P. Oguntoye
%A O.O. Awodoye
%A M.O. Oyewole
%T Development of a Plant Disease Classification System using an Improved Counter Propagation Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 20
%P 19-26
%D 2020
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Plant diseases are a major threat to food security and can be precisely and accurately recognized through the images of plant leaves. The recent advances in computer vision made possible by the various computational method have paved the way for computer-assisted disease diagnosis. Thus, automated recognition of diseases on leaves plays a crucial role in the agriculture sector. Counter Propagation Neural Network (CPN) is highly desirable because it comprises the advantages of supervised and unsupervised training approaches. CPN in most image processing application guarantee high accuracy but consume more time for convergence. In this study, the development of a plant disease classification system using an improved Counter Propagation Neural Network (CPN) technique was carried out. Gravitational Search Algorithm (GSA) was applied to optimize the network of CPN for improved performance. The approach adopted in this study enhances CPN by making it free from the iterative adjustment of weights which increases the computational speed to a higher extent. The experimental results reveal that the proposed technique achieved improved performance in terms of recognition accuracy and prediction time.

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Index Terms

Computer Science
Information Sciences

Keywords

Counter Propagation Neural Network Gravitational Search Algorithm Plant Diseases Image Processing.

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