Multispectral and Hyperspectral Reflectance Imaging Spectrometry (VIS, VNIR, SWIR) in Painting Analyses: Undergraduate Teaching and Interfacial Undergraduate Research at the Nexus of Chemistry and Art

Uffelman, Erich S.; Abraham, Liesbeth; Davis, J. P.; Delaney, John K.; Dooley, Kathryn A.; Hewitt, Lindsey; Koenen, Jorinde; Marvelde, Mireille te; Muensterman, Kathryn; Oikonomou, Konstantinos; Olmstead, Darcy; Perdue, Trinity; Rocha, Jensen; Roeders, Jessica; Roy, Annika; Speleers, Lidwien

doi:10.1021/bk-2021-1386.ch009

ACS Symposium Series

2021

DOI: 10.1021/bk-2021-1386.ch009

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Multispectral and Hyperspectral Reflectance Imaging Spectrometry (VIS, VNIR, SWIR) in Painting Analyses: Undergraduate Teaching and Interfacial Undergraduate Research at the Nexus of Chemistry and Art

Erich S. Uffelman

Liesbeth Abraham²,

J. P. Davis

et al.

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Methodological approach for the automatic discrimination of pictorial materials using fused hyperspectral imaging data from the visible to mid-infrared range coupled with machine learning methods

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Methodological approach for the automatic discrimination of pictorial materials using fused hyperspectral imaging data from the visible to mid-infrared range coupled with machine learning methods

Capobianco,

Pronti,

Gorga

et al. 2024

Spectrochimica Acta Part A: Molecular and Biomolecular Spectros

View full text Add to dashboard Cite

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Multispectral and Hyperspectral Reflectance Imaging Spectrometry (VIS, VNIR, SWIR) in Painting Analyses: Undergraduate Teaching and Interfacial Undergraduate Research at the Nexus of Chemistry and Art

Cited by 1 publication

References 80 publications

Methodological approach for the automatic discrimination of pictorial materials using fused hyperspectral imaging data from the visible to mid-infrared range coupled with machine learning methods

Methodological approach for the automatic discrimination of pictorial materials using fused hyperspectral imaging data from the visible to mid-infrared range coupled with machine learning methods

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