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An unsupervised material learning method for imaging spectroscopy

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]

CollectionsANU Research Publications
Date published: 2014
Type: Conference paper
Source: Proceedings of the International Joint Conference on Neural Networks
DOI: 10.1109/IJCNN.2014.6889441


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