DocumentCode :
2951193
Title :
FPGA Based LIRA Neural Classifier
Author :
Vega, Alejandro ; Baidyk, Tatiana ; Kussul, Ernst ; Silva, José Luis Pérez
Author_Institution :
Center of Appl. Sci. & Technol. Dev., Nat. Autonomous Univ. of Mexico (UNAM), Mexico City, Mexico
fYear :
2011
fDate :
15-18 Nov. 2011
Firstpage :
65
Lastpage :
70
Abstract :
Neural networks can be used for image classification. They are powerful instruments in image and pattern recognition because they have following advantages: parallel structure, training in the process of the classifier preparation, and possibility to implement them as an electronic circuit. A special type of neural classifier, LIRA (Limited Receptive Area) neural classifier, has been developed and used to solve different tasks, for example, handwritten digit recognition, face recognition, texture and shape recognition, etc. It is important to reduce the time of system work so the neural classifier was implemented in a FPGA device.
Keywords :
face recognition; field programmable gate arrays; handwriting recognition; image classification; image texture; neural nets; shape recognition; FPGA; LIRA neural classifier; classifier preparation; electronic circuit; face recognition; handwritten digit recognition; image classification; image recognition; limited receptive area; neural networks; parallel structure; pattern recognition; shape recognition; texture recognition; Biological neural networks; Face recognition; Field programmable gate arrays; Handwriting recognition; Image recognition; Neurons; Random access memory; LIRA neural classifier; logic circuits; neural networks; neuron;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference (CERMA), 2011 IEEE
Conference_Location :
Cuernavaca, Morelos
Print_ISBN :
978-1-4577-1879-3
Type :
conf
DOI :
10.1109/CERMA.2011.18
Filename :
6125800
Link To Document :
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