Title :
Object recognition on general purposed Conic Section Function Neural Network integrated circuit
Author :
Vural, Revna Acar ; Kahraman, Nihan ; Erkmen, Burcu ; Yildirim, Tülay
Author_Institution :
Elektron. ve Haberlesme Muhendisligi Bolumu, Yildiz Teknik Univ., Istanbul
Abstract :
Automatic recognition using a database obtained from existing objects is getting more importance for industrial and security applications. In this work, the database is collected from the images of various objects that are rotated at different angles have been tested on a general purposed conic section function neural network (CSFNN) integrated circuit. Both hardware results of the integrated circuit and the software results of CSFNN have been compared and applicability of the designed integrated circuit to the object recognition problem has been demonstrated.
Keywords :
integrated circuits; neural nets; object recognition; general purposed conic section function; industrial applications; neural network integrated circuit; object recognition; security applications; Application software; Circuit testing; Data security; Hardware; Image databases; Integrated circuit testing; Neural networks; Object recognition; Very large scale integration;
Conference_Titel :
Signal Processing, Communication and Applications Conference, 2008. SIU 2008. IEEE 16th
Conference_Location :
Aydin
Print_ISBN :
978-1-4244-1998-2
Electronic_ISBN :
978-1-4244-1999-9
DOI :
10.1109/SIU.2008.4632598
