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

Authors

  • G.D. Jasmin

  • E.G. Rajan

Keywords:

pattern recognition, formal representation of images, object recognition

Abstract

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.

How to Cite

G.D. Jasmin, & E.G. Rajan. (2013). Normalized Vector Codes for Object Recognition Using Artificial Neural Networks in the Framework of Picture Description Languages. Global Journal of Computer Science and Technology, 13(D2), 25–33. Retrieved from https://computerresearch.org/index.php/computer/article/view/362

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

Published

2013-05-15