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Reseach Article

Performance Evaluation of Classification Techniques for Computer Vision based Cashew Grading System

by Mayur Thakkar, Malay Bhatt, C. K. Bhensdadia
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 18 - Number 6
Year of Publication: 2011
Authors: Mayur Thakkar, Malay Bhatt, C. K. Bhensdadia
10.5120/2291-2975

Mayur Thakkar, Malay Bhatt, C. K. Bhensdadia . Performance Evaluation of Classification Techniques for Computer Vision based Cashew Grading System. International Journal of Computer Applications. 18, 6 ( March 2011), 9-12. DOI=10.5120/2291-2975

@article{ 10.5120/2291-2975,
author = { Mayur Thakkar, Malay Bhatt, C. K. Bhensdadia },
title = { Performance Evaluation of Classification Techniques for Computer Vision based Cashew Grading System },
journal = { International Journal of Computer Applications },
issue_date = { March 2011 },
volume = { 18 },
number = { 6 },
month = { March },
year = { 2011 },
issn = { 0975-8887 },
pages = { 9-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume18/number6/2291-2975/ },
doi = { 10.5120/2291-2975 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:05:34.462232+05:30
%A Mayur Thakkar
%A Malay Bhatt
%A C. K. Bhensdadia
%T Performance Evaluation of Classification Techniques for Computer Vision based Cashew Grading System
%J International Journal of Computer Applications
%@ 0975-8887
%V 18
%N 6
%P 9-12
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The performance of various classification algorithms greatly depends on the characteristics of the data to be classified. There is no single classifier that works best on all given problems. The purpose of this study is to develop the computer vision based whole cashew grading system in conjunction with most accurate classification technique. The performance of different classification techniques including Multi-Layer Perceptron, Naive Bayes, K-Nearest Neighbor, Decision tree, Support Vector Machine are evaluated using WEKA toolbox to have most suitable classification technique for the cashew grading system. Subsequently, the classification technique that has the potential to significantly improve the performance of the system is suggested to be utilized in cashew grading system.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Cashew grading system Decision tree k-Nearest Neighbors Multi-Layer Perceptron (MLP) Naïve Bayes Support Vector Machine (SVM)