Normalized Vector Codes for Object Recognition Using Artificial Neural Networks in the Framework of Picture Description Languages

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G.D. Jasmin
G.D. Jasmin
2
E.G. Rajan
E.G. Rajan
1 Mysore University

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Your Understanding how biological visual systems recognize objects is one of the ultimate goals in computational neuroscience. People are able to recognize different types of objects despite the fact that the objects may vary in view, points, sizes, scale, texture or even when they are translated or rotated. In this paper we focus on syntactic approach for the description of objects as Normalized Vector Codes using which objects are recognized based on their shapes.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

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Not applicable for this article.

G.D. Jasmin. 2013. \u201cNormalized Vector Codes for Object Recognition Using Artificial Neural Networks in the Framework of Picture Description Languages\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 13 (GJCST Volume 13 Issue D2): .

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GJCST Volume 13 Issue D2
Pg. 25- 33
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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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v1.2

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May 19, 2013

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English

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Your Understanding how biological visual systems recognize objects is one of the ultimate goals in computational neuroscience. People are able to recognize different types of objects despite the fact that the objects may vary in view, points, sizes, scale, texture or even when they are translated or rotated. In this paper we focus on syntactic approach for the description of objects as Normalized Vector Codes using which objects are recognized based on their shapes.

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Normalized Vector Codes for Object Recognition Using Artificial Neural Networks in the Framework of Picture Description Languages

G.D. Jasmin
G.D. Jasmin Mysore University
E.G. Rajan
E.G. Rajan

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