Raman spectrum matching with contrastive representation learning

Raman spectroscopy is an important, low-cost, non-intrusive technique often used for chemical identification. Typical approaches identify a spectrum by comparing it with a reference database using supervised machine learning, which usually requires careful preprocessing and multiple spectra availabl...

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Veröffentlicht in:	Analyst (London) 2022-05, Vol.147 (1), p.2238-2246
Hauptverfasser:	Li, Bo, Schmidt, Mikkel N, Alstrøm, Tommy S
Format:	Artikel
Sprache:	eng
Schlagworte:	Datasets Machine learning Matching Preprocessing Raman spectroscopy Representations Spectrum analysis
Online-Zugang:	Volltext
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