Mohamed Ezz, Waad Alanazi, Ayman Mohamed Mostafa*, Eslam Hamouda, Murtada K. Elbashir, Meshrif Alruily
Computer Systems Science and Engineering, Vol.46, No.2, pp. 2299-2317, 2023, DOI:10.32604/csse.2023.036567
Abstract Palmprint identification has been conducted over the last two decades in many biometric systems. High-dimensional data with many uncorrelated and duplicated features remains difficult due to several computational complexity issues. This paper presents an interactive authentication approach based on deep learning and feature selection that supports Palmprint authentication. The proposed model has two stages of learning; the first stage is to transfer pre-trained VGG-16 of ImageNet to specific features based on the extraction model. The second stage involves the VGG-16 Palmprint feature extraction in the Siamese network to learn Palmprint similarity. The proposed model achieves robust and reliable end-to-end Palmprint… More >
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