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Hidden Markov Random Fields and classification of land use with satellite image data Dr. Jason Stover, GC Mathematics Department


Abstract

In this talk, I will define Markov Random Fields and show how they can be used to infer land use via reflectivity data. Data from satellite images contain information about the reflectivity of the surface of the Earth, which must then be used to infer the use of the land corresponding to particular pixels. One possible approach is to treat the land use as an example of a Markov Random Field, whose true value is unknown except through the observed reflectivity.
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