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OpenVeinNet advances open-set finger vein verification with novel deep learning techniques

By PulseAugur Editorial · [2 sources] ·

Researchers have introduced OpenVeinNet, a novel framework for robust open-set finger vein verification. This system combines Dynamic Snake Convolution for extracting local vein structures with graph-based modeling to capture topological relationships between vein regions. To enhance the discriminative power of its embedding space, OpenVeinNet utilizes a Centroid Angular Hybrid Loss function. Experiments across multiple datasets demonstrate OpenVeinNet's strong cross-dataset generalization capabilities and low error rates, indicating its effectiveness for secure biometric authentication. AI

IMPACT Enhances biometric security by improving the accuracy and robustness of finger vein identification systems.

RANK_REASON The cluster describes a research paper detailing a new model and methodology for finger vein verification.

Read on Hugging Face Daily Papers →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

OpenVeinNet advances open-set finger vein verification with novel deep learning techniques

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The cluster describes a research paper detailing a new model and methodology for finger vein verification.
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46 days old
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COVERAGE [2]

  1. Hugging Face Daily Papers TIER_1 English(EN) ·

    OpenVeinNet: Robust Open-Set Finger Vein Verification with Dynamic Snake Convolution and Graph Learning

    Finger vein verification is a promising biometric modality for secure authentication because vascular patterns are internal, difficult to observe externally, and relatively resistant to presentation attacks. However, reliable verification remains challenging in open-set settings,…

  2. arXiv cs.CV TIER_1 English(EN) · Sushrut Patwardhan, Raghavendra Ramachandra ·

    OpenVeinNet: Robust Open-Set Finger Vein Verification with Dynamic Snake Convolution and Graph Learning

    arXiv:2608.25515v1 Announce Type: new Abstract: Finger vein verification is a promising biometric modality for secure authentication because vascular patterns are internal, difficult to observe externally, and relatively resistant to presentation attacks. However, reliable verifi…

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