Study of a Committee of Neural Networks for Biometric Hand-Geometry Recognition

摘要

This Paper studies different committees of neural networks for bio-metric pattern recognition. We use the neural nets as classifiers for identification and verification purposes. We show that a committee of nets can improve the recognition rates when compared with a multi-start initialization algorithm that just picks up the neural net which offers the best performance. On the other hand, we found that there is no strong correlation between identification and verification applications using the same classifier.