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3-D Object Recognition Using 2-D Poses Processed by CNNs and a GRNN

  • Övünç Polat
  • Vedat Tavşanoğlu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3949)

Abstract

This paper presents a novel approach to automatically recognize objects. The system used is a new model that contains two blocks; one for extracting direction and pixel features from object images using Cellular Neural Networks (CNN), and the other for classification of objects using a General Regression Neural Network (GRNN). A data set consisting of different properties of 10 different objects is prepared by CNN.

Keywords

Feature Vector Object Recognition Recognition Rate Radial Basis Function Neural Network Object Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Övünç Polat
    • 1
  • Vedat Tavşanoğlu
    • 1
  1. 1.Electronics and Communications Engineering DepartmentYıldız Technical UniversityBesiktas, IstanbulTurkey

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