Understanding the Impact of Evaluation Metrics in Kinetic Models for Consensus-Based Segmentation

In this article, we extend a recently introduced kinetic model for consensus-based segmentation of images. In particular, we will interpret the set of pixels of a 2D image as an interacting particle system that evolves in time in view of a consensus-type process obtained by interactions between pixe...

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Bibliographic Details
Main Authors: Raffaella Fiamma Cabini, Horacio Tettamanti, Mattia Zanella
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Entropy
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Online Access:https://www.mdpi.com/1099-4300/27/2/149
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Summary:In this article, we extend a recently introduced kinetic model for consensus-based segmentation of images. In particular, we will interpret the set of pixels of a 2D image as an interacting particle system that evolves in time in view of a consensus-type process obtained by interactions between pixels and external noise. Thanks to a kinetic formulation of the introduced model, we derive the large time solution of the model. We will show that the parameters defining the segmentation task can be chosen from a plurality of loss functions that characterize the evaluation metrics.
ISSN:1099-4300