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ISNN
2005
Springer

Application of Multi-weighted Neuron for Iris Recognition

14 years 5 months ago
Application of Multi-weighted Neuron for Iris Recognition
Abstract. In this paper, from the cognition science point of view, we constructed a neuron of multi-weighted neural network, and proposed a new method for iris recognition based on multi-weighted neuron. In this method, irises are trained as “cognition” one class by one class, and it doesn’t influence the original recognition knowledge for samples of the new added class. The results of experiments show the correct rejection rate is 98.9%, the correct cognition rate and the error recognition rate are 95.71% and 3.5% respectively. The experimental results demonstrate that the correct rejection rate of the test samples excluded in the classes of training samples is very high. It proves the proposed method for iris recognition is effective.
Wenming Cao, Jianhui Hu, Gang Xiao, Shoujue Wang
Added 27 Jun 2010
Updated 27 Jun 2010
Type Conference
Year 2005
Where ISNN
Authors Wenming Cao, Jianhui Hu, Gang Xiao, Shoujue Wang
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