Deep learning techniques for hand vein biometrics: A comprehensive review

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Mustapha Hemis, Hamza Kheddar, Sami Bourouis, Nasir Saleem

Published: 01 Jan 2025, Last Modified: 19 Oct 2025Inf. Fusion 2025EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: Highlights•Hand vein biometrics provide high accuracy, low forgery risk, and non-intrusiveness.•Review explores DL techniques for FV, PV, DHV, and multimodal vein recognition.•Covers datasets, SOTA metrics, and best-performing vein recognition methods.•Insights on data augmentation techniques, TL, and pretrained DL models provided.•Discusses research challenges and future directions.