Genetic algorithm fine tuning of Support Vector Data Descriptor (SVDD) for classification of monocotyledon and dicotyledon weeds

Wong, Wei Kitt and Muralindran Mariappan, and Chekima Ali, and Khoo, Brendan and Manimehala Nadarajan, (2014) Genetic algorithm fine tuning of Support Vector Data Descriptor (SVDD) for classification of monocotyledon and dicotyledon weeds. International Journal of Enhanced Research in Science Technology & Engineering, 3 (8). pp. 201-205. ISSN 2319-7463

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Abstract

Weed recognition using image processing has been performed and improved in various papers. In this paper, weed seedlings were discriminated using Support Vector Data Descriptor (SVDD) to identify monocotyledon weeds from mixture of monocotyledon and dicotyledon weeds. The feature selection and parameter fine tuning were performed using genetic Algorithm (GA). The resulting SVDD configurations were tested using 200 image samples. The best configurations gave an average of 95% recognition rate.

Item Type: Article
Uncontrolled Keywords: Support Vector Data Descriptor (SVDD), Genetic Algorithm (GA)
Subjects: Q Science > QK Botany
Divisions: FACULTY > Faculty of Engineering
Depositing User: Munira
Date Deposited: 20 Jun 2018 00:23
Last Modified: 20 Jun 2018 00:23
URI: http://eprints.ums.edu.my/id/eprint/20215

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