A quasi-concavity formulation turns global convexity into local differentiable inequalities on a segmentation mask and its derivatives, yielding a convolutional loss that unifies prior convex shape models.
A binary characterization method for shape convex- ity and applications.Applied Mathematical Modelling, 122: 780–795, 2023
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D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentation
A quasi-concavity formulation turns global convexity into local differentiable inequalities on a segmentation mask and its derivatives, yielding a convolutional loss that unifies prior convex shape models.