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Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine

by Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 181 - Number 13
Year of Publication: 2018
Authors: Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur
10.5120/ijca2018917746

Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur . Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine. International Journal of Computer Applications. 181, 13 ( Aug 2018), 31-36. DOI=10.5120/ijca2018917746

@article{ 10.5120/ijca2018917746,
author = { Nabodip Sutrodhor, Molla Rashied Hussein, Md. Firoz Mridha, Prokash Karmokar, Tasrifa Nur },
title = { Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2018 },
volume = { 181 },
number = { 13 },
month = { Aug },
year = { 2018 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume181/number13/29880-2018917746/ },
doi = { 10.5120/ijca2018917746 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:05:54.663746+05:30
%A Nabodip Sutrodhor
%A Molla Rashied Hussein
%A Md. Firoz Mridha
%A Prokash Karmokar
%A Tasrifa Nur
%T Mango Leaf Ailment Detection using Neural Network Ensemble and Support Vector Machine
%J International Journal of Computer Applications
%@ 0975-8887
%V 181
%N 13
%P 31-36
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a Neural Network Ensemble (NNE) for Mango Leaf Ailment Detection (MLAD) system. At first, the images of Mango leaves were cropped, then were resized and converted to their value of threshold. After that, the feature extraction methodology was applied. For pattern recognition, NNE and SVM were used. Subsequently, test images of affected leaves were uploaded to the system and then were matched to the trained ailments. The training data and test data were cross-validated to sustain equilibrium among over-fitting and under-fitting issues.

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Index Terms

Computer Science
Information Sciences

Keywords

Neural Network Ensemble Pattern Recognition Support Vector Machine Mango Leaf Ailment Detection Image Processing Automated System

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