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Archive / INF Seminars / INF_2025_09_04_Tettamanti

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	Kinetic Methods for Consensus-Based Segmentation

Host: Prof. Michael Multerer

Thursday

04.09

USI Campus EST, Room D0.03

15:30 - 16:30


	Horacio Tettamanti Department of Mathematics, University of Pavia, Italy

Abstract: Image Segmentation is a fundamental task in the context of image processing and computer vision that consists of partitioning an image into subsets of pixels that share similar properties so as to facilitate the analysis and interpretation of the visual data. The application of image segmentation methods plays an important role in clinical research by facilitating the study of anatomical structures, highlighting regions of interest, and measuring tissue volume. In this talk Mr. Tettamanti will present a new approach based on Consensus-Based Models for the Image Segmentation task. By considering the pixels of an image as an interacting system where each particle is characterized by its space position and a feature determining the gray level, a virtual interaction between the particles will then determine the asymptotic formation of a finite number of clusters.
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Biography: Horacio Tettamanti received his Physics degree in 2024 at the University of Buenos Aires where he worked in the resolution of Blow-up type PDEs through the use of Physics Informed Neural Network. In October, 2024 he began his PHD under the supervision of Prof. Mattia Zanella at the University of Pavia and its currently working in various of applications of interacting agent-based systems.