Deep learning model based on inceptionResnet-v2 for Finger vein recognition

In recent years, The pattern of finger veins is widely
recognized as an effective biometric for identifying a person. The
traditional finger vein identification systems are based on hand-
crafted features. However, Finger vein systems has been switched
toward automatic features extraction due to the emergence of
deep neural networks that are capable of extracting deep features.
In this paper, an inceptionResnet-v2 pre-trained deep convolution
neural network model is proposed for finger vein identification.
We tested the performance of the proposed model on the public
Finger vein databases SDUMLA, MMCBNU and FV-USM. The
obtained results indicate the effectiveness and security of the
proposed network as it has achieved very small errors for all
data sets