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| LEADER |
01512 am a22002173u 4500 |
| 001 |
66818 |
| 042 |
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|a dc
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| 100 |
1 |
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|a Chua, Lee Suan
|e author
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| 700 |
1 |
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|a Alias, Norma
|e author
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| 700 |
1 |
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|a Januari, Ristian
|e author
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1 |
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|a Mustaffa, Maizatul Nadirah
|e author
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| 700 |
1 |
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|a Ali, Akhtar
|e author
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| 700 |
1 |
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|a Ahmad Kamal, Mohamad Hidayad
|e author
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| 700 |
1 |
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|a Hayat, Imran
|e author
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| 245 |
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|a Mathematical modeling for contour identification based on medicinal leaves and GIS images
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| 260 |
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|b Penerbit UTM Press,
|c 2016-01-11.
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| 856 |
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|z Get fulltext
|u http://eprints.utm.my/id/eprint/66818/1/NormaAlias2016_MathematicalModelingforContourIdentification.pdf
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|a In this paper, the identification of contour medicinal leaves and GIS images has been determined. The purposes of the Geodesic Active Contour-Additive Operating Splitting (GAC-AOS) modelling are to identify an unknown type of medicinal leaves and edge detection of our images. Besides, three iterative methods such as SOR, RBGS and Jacobi method are used to solve the linear system of equations. In the implementation of the GAC-the AOS model, the experimental result demonstrates that the SOR method gives the best performance compared to the other two methods. The computation platform is based on Intel® CoreTM Duo Processor Architecture with MATLAB version R2011a. The performance analysis is based on the iteration numbers, execution time, accuracy and RMSE.
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| 546 |
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|a en
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| 650 |
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|a Q Science
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|a TP Chemical technology
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