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Case Studies on Neural Networks for Recognition in Biometric Identity Problem

Zhengwen Shen, Jun Wang, Zaiyu Pan, Kai Yang

Abstract: Hand-dorsa vein recognition using a convolutional neural network is presented. Our network contains five convolutional layers and three full connected layers, which have high recognition and more robust. The experimental results on the self-established database with the proposed CNN achieves 98.02% in training part and 97.65% in testing part, which demonstrates the effectiveness of the proposed CNN.
Keywords: neural / vein / convolutional / robust / experimental / Biometric / dorsa / proposed CNN / full connected layers

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