Neural network-based classification of X-ray fluorescence spectra of artists’ pigments: an approach leveraging a synthetic dataset created using the fundamental parameters method

Neural network-based classification of X-ray fluorescence spectra of artists’ pigments: an approach leveraging a synthetic dataset created using the fundamental parameters method

Abstract X-ray fluorescence (XRF) spectroscopy is an analytical technique used to identify chemical elements that has found widespread use in the cultural heritage sector to characterise artists' materials including the pigments in paintings. It generates a spectrum with characteristic emission...

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Bibliographic Details
Main Authors: Cerys Jones, Nathan S. Daly, Catherine Higgitt, Miguel R. D. Rodrigues
Format: Article
Language:English
Published: SpringerOpen 2022-06-01
Series:Heritage Science
Subjects:
X-ray fluorescence
Convolutional neural networks
Deep learning
Transfer learning
Classification
Synthetic data
Online Access:https://doi.org/10.1186/s40494-022-00716-3

Internet

https://doi.org/10.1186/s40494-022-00716-3

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