论文标题
生物特征识别识别委员会的神经网络委员会的研究
Study of a committee of neural networks for biometric hand-geometry recognition
论文作者
论文摘要
本文研究了神经网络的不同委员会，以识别生物识别模式识别。我们将神经网作为分类器来识别和验证目的。我们表明，与多开始的初始化算法相比，网络委员会可以提高识别率，该初始化算法算法算法，该初始化算法只能获得最佳性能的神经网。另一方面，我们发现使用同一分类器之间的识别应用程序和验证应用程序之间没有很强的相关性。
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.
