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Open access Jul 2026

Graph-Regularized Low-Rank Label Correlation Learning with Label-Specific Features for Missing Labels

Missing labels are common in multi-label learning and can bias both label-correlation estimation and classifier induction. Existing missing-label methods often recover incomplete supervision mainly through global label correlations. However, correlation-driven recovery alone may produce over-smoothed supervision when a...

Tian-Lin Li, M. F. Nasrudin, Xing-Lin Peng et al. · 0 citations
Open access Aug 2026

Dual semantic consistency module for domain generalizable face anti-spoofing

The proposed DSCM-FAS is a novel framework that combines inter-sample and intra-sample semantic consistency to enhance robustness and cross-domain generalization, without requiring auxiliary supervision, and demonstrates that DSCM-FAS consistently outperforms state-of-the-art methods under various protocols.

Hui Xing, Siok Yee Tan, Faizan Qamar et al. · 0 citations

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