A neural network trained only on simulated spectra detects weak, blended, and ringing-distorted lines in experimental FT atomic spectra, recovering roughly 95% of human-found lines and enabling two new Ni II level identifications.
2005 Physica Scripta 2005 19
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A neural network approach for line detection in complex atomic emission spectra measured by high-resolution Fourier transform spectroscopy
A neural network trained only on simulated spectra detects weak, blended, and ringing-distorted lines in experimental FT atomic spectra, recovering roughly 95% of human-found lines and enabling two new Ni II level identifications.