Cabini, Raffaella Fiamma Tettamanti, Horacio Zanella, Mattia 2025 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. application/pdf https://n2t.net/ark:/12658/srd1331832 https://susi.usi.ch/global/documents/331832 https://susi.usi.ch/documents/331832/files/Cabini_2025_MDPI_entropy_Understanding the impact.pdf eng info:eu-repo/semantics/altIdentifier/doi/10.3390/e27020149 info:eu-repo/semantics/altIdentifier/ark/12658/srd1331832 info:eu-repo/semantics/openAccess CC BY Entropy. - 2025, vol. 27, no. 2, p. 149 Kinetic equations Interacting particle systems Consensus models Image segmentation Clustering info:eu-repo/classification/udc/51 Understanding the impact of evaluation metrics in kinetic models for consensus-based segmentation http://purl.org/coar/resource_type/c_6501