Hybrid CNN with angular margin supervision for robust face identification and verification
Face recognition systems are widely used in surveillance, biometric authentication, access control, and digital identity verification; however, supervision sensitivity, evaluation stability, and performance consistency across datasets remain insufficiently understood. This study investigates the behavior of convolutional, transformer-based, and hybrid face recognition architectures under both Softmax and ArcFace supervision using five-fold subject-disjoint cross-validation on the Labeled Faces i
Record details
Published: 27 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Privacy · Finance, VC & PE
Retrieved: 28 July 2026
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ethics.ai (27 July 2026), “Hybrid CNN with angular margin supervision for robust face identification and verification,” evidence record 13874, https://ethics.ai/record/13874 (originally published by Frontiers in Artificial Intelligence).
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