Paper:	Neural Network for Stellar Spectrum Normalization
Volume:	532, ASTRONOMICAL DATA ANALYSIS SOFTWARE AND SYSTEMS XXX
Page:	251
Authors:	Rozanski, T.; Niemczura, E.; Posilek, N.
Abstract:	We present a deep fully convolutional neural network trained in the task of stellar spectrum normalization. We show that the proposed model is able to fit spectral continuum, including non-smooth instrumental pseudo-continuum, wide hydrogen, and narrow blended spectral lines. Proposed solution gives an opportunity to automate this step of stellar spectrum preprocessing, and achieve the accuracy similar to that of careful manual normalization. This approach may greatly simplify automated high-resolution spectra analysis.

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