Web: http://arxiv.org/abs/2205.02938

May 9, 2022, 1:11 a.m. | Alessandro Lonardi, Diego Baptista, Caterina De Bacco

cs.LG updates on arXiv.org arxiv.org

In classification tasks, it is crucial to meaningfully exploit information
contained in data. Here, we propose a physics-inspired dynamical system that
adapts Optimal Transport principles to effectively leverage color distributions
of images. Our dynamics regulates immiscible fluxes of colors traveling on a
network built from images. Instead of aggregating colors together, it treats
them as different commodities that interact with a shared capacity on edges.
Our method outperforms competitor algorithms on image classification tasks in
datasets where color information matters.

arxiv classification color cv image networks transport

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