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InfoResearchPeer-reviewed
Deep Physiological–Behavioral Representation Learning for Dynamic Hand Gesture Authentication
- Published
- Record updated
Summary
PB-Net v2 is a revised dynamic hand gesture authentication model that refines data tailoring, the physiological and behavioral branches, and the feature fusion module. On SCUT-DHGA, SCUT-DHGA-br, and SCUT-RealDHGA, it achieves the lowest equal error rates among 22 state-of-the-art models under four evaluation protocols. It also shows improved robustness against imitation-oriented spoofing attacks under three such protocols.