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Malaysia–Japan International Institute of Technology, University Teknologi Malaysia, Kuala Lumpur, Malaysia
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Classifying one-class classification models reveals that dataset characteristics can significantly influence model performance, challenging traditional views on model evaluation.
PANC achieves a staggering 162% increase in attack effectiveness against Transformer-based visual trackers while slashing noise levels to just 10%.
