Deep learning for near-infrared spectral data modelling: Hypes and benefits

Deep learning (DL) is emerging as a new tool to model spectral data acquired in analytical experiments. Although applications are flourishing, there is also much interest currently observed in the scientific community on the use of DL for spectral data modelling. This paper provides a critical and c...

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Veröffentlicht in:	TrAC, Trends in analytical chemistry (Regular ed.) Trends in analytical chemistry (Regular ed.), 2022-12, Vol.157, p.116804, Article 116804
Hauptverfasser:	Mishra, Puneet, Passos, Dário, Marini, Federico, Xu, Junli, Amigo, Jose M., Gowen, Aoife A., Jansen, Jeroen J., Biancolillo, Alessandra, Roger, Jean Michel, Rutledge, Douglas N., Nordon, Alison
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial intelligence Chemometrics data collection guidelines Life Sciences Near-infrared Neural networks NIR spectral analysis Spectroscopy
Online-Zugang:	Volltext
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