3-D object recognition using 2-D poses processed by CNNs and a GRNN

POLAT Ö., Tavşanoğlu V.

ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS, cilt.3949, ss.219-226, 2006 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 3949
  • Basım Tarihi: 2006
  • Dergi Adı: ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.219-226
  • Akdeniz Üniversitesi Adresli: Hayır

Özet

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.