Staff Members - Benha University
R. M. Farouk , E. M. Badr and M. A. SayedElahl (2014) "RECOGNITION OF CDNA MICROARRAY IMAGE USING FEEDFORWARD ARTIFICIAL NEURAL NETWORK " International Journal of Artificial Intelligence & Applications (IJAIA), Vol. 5, No. 5, September 2014
• 2014
Publication Information
Authors
R. M. Farouk , E. M. Badr and M. A. SayedElahl
Keywords
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Journal
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Volume
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Pages
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publication.type
International
Paper Link
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Supplementary Materials
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Abstract
The complementary DNA (cDNA) sequence considered the magic biometric technique for personal identification. Microarray image processing used for the concurrent genes identification. In this paper, we present a new method for cDNA recognition based on the artificial neural network (ANN). We have
segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the
proposed artificial neural network. For matching and recognition, we have trained the artificial neural
network. Recognition results are given for the galleries of cDNA sequences . The numerical results show that, the proposed matching technique is an effective in the cDNA sequences process. The experimental results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.
segmented the location of the spots in a cDNA microarray. Thus, a precise localization and segmenting of a spot are essential to obtain a more exact intensity measurement, leading to a more accurate gene expression measurement. The segmented cDNA microarray image resized and used as an input for the
proposed artificial neural network. For matching and recognition, we have trained the artificial neural
network. Recognition results are given for the galleries of cDNA sequences . The numerical results show that, the proposed matching technique is an effective in the cDNA sequences process. The experimental results of our matching approach using different databases shows that, the proposed technique is an effective matching performance.