Using CNNs to Identify the Origin of Finger Vein Sample Images
arXiv (Cornell University)(2021)
Abstract
We study the finger vein (FV) sensor model identification task using a deep learning approach. So far, for this biometric modality, only correlation-based PRNU and texture descriptor-based methods have been applied. We employ five prominent CNN architectures covering a wide range of CNN family models, including VGG16, ResNet, and the Xception model. In addition, a novel architecture termed FV2021 ...
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Key words
Deep learning,Biometrics (access control),Databases,Veins,Biological system modeling,Forensics,Conferences
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