Title :
Fuzzy art neural network model and its application
Author_Institution :
Dept. of Software Eng., ShenZhen Polytech., Shenzhen, China
Abstract :
The model based on fuzzy ART neural network is designed and realized. It can deal with online learning and recognition of the known and unknown faces at the same time. The simulation experiment results show an online maximum recognition rate is 91.25% when the proper network parameters are selected. 400 images of 40 persons in the AT&T Yale face database are used for simulation experiment.
Keywords :
face recognition; fuzzy neural nets; learning (artificial intelligence); AT&T Yale face database; face recognition; fuzzy adaptive resonance theory neural network model; online learning; simulation experiment; Application software; Art; Face detection; Face recognition; Fuzzy neural networks; Fuzzy systems; Humans; Neural networks; Spatial databases; Subspace constraints; Algorithm; Face recognition; Fuzzy ART; Neural network; Online training;
Conference_Titel :
Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-4754-1
Electronic_ISBN :
978-1-4244-4738-1
DOI :
10.1109/ICICISYS.2009.5357895
