DLED reformulates open-set face forgery detection as an uncertainty estimation task and uses dual-level spatial-frequency evidence collection to identify novel fake categories, claiming 20% average gains over baselines.
Toward open set recogni- tion.IEEE transactions on pattern analysis and machine intelligence, 35(7):1757–1772, 2012
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TaxoNet uses a dual-margin objective to reshape decision boundaries in long-tailed fine-grained plant taxonomy, improving rare-class geometry under open-world conditions.
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Open Set Face Forgery Detection via Dual-Level Evidence Collection
DLED reformulates open-set face forgery detection as an uncertainty estimation task and uses dual-level spatial-frequency evidence collection to identify novel fake categories, claiming 20% average gains over baselines.
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Dual-Margin Embedding for Fine-Grained Long-Tailed Plant Taxonomy
TaxoNet uses a dual-margin objective to reshape decision boundaries in long-tailed fine-grained plant taxonomy, improving rare-class geometry under open-world conditions.