Quantitative analysis of energy-dispersive X-ray fluorescence spectroscopy based on machine learning and a generative data enhancement technique

This paper proposes a data enhancement technique to generate expanded datasets for machine learning by developing an X-ray fluorescence spectra simulator based on the physical process. The simulator consists of several modules, including the excitation source, the interaction process, and the detect...

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Veröffentlicht in:	Applied optics (2004) 2023-12, Vol.62 (36), p.9476-9485
Hauptverfasser:	Zhao, Wei, Ai, Xianyun, Zhao, Hui
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Datasets Feature extraction Machine learning Simulation Spectra Spectrum analysis X ray fluorescence analysis
Online-Zugang:	Volltext
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