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 has been developed as a specialized tool for evaluating entropy-based uncertainty in image segmentation tasks. However%2C our investigation identifies three core deficiencies within the PAvPU framework and proposes robust solutions aimed at refining the metric. By addressing these issues%2C we aim to enhance the reliability and applicability of uncertainty quantification%2C especially in scenarios that demand high levels of safety and accuracy%2C thus contributing to the advancement of semantic segmentation methodologies in critical applications.?quality=80&w=800)
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