  This Paper studies different committees of neural networks for biometric
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 algo-rithm
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
identifi-cation and verification applications using the same classifier.
