Jordan, Johannes; Angelopoulou, Elli; Robles-Kelly, Antonio
In this paper we propose a method for learning the materials in a scene in an unsupervised manner making use of imaging spectroscopy data. Here, we view the input image spectra as a data point on a manifold which corresponds to a node in a graph whose vertices correspond to a set of parameters that should be inferred using the Expectation Maximisation (EM) algorithm. In this manner, we can pose the problem as a statistical unsupervised learning one where the aim of computation becomes the...[Show more]
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