Abstract

In this paper a machine learning method Gaussian process regression (GPR) is applied to directly learn the mapping between the measured spectrum and the temperature. A comparison with other conventional methods is performed and it is shown that the GPR based method gives a better performance in cases with low noise.

© 2018 The Author(s)

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