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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 compresses adversarial noise to just 10%, boosting attack effectiveness by 162% while minimizing query counts, exposing critical weaknesses in Transformer-based visual trackers.
