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Volume: 17 | Article ID: art00007
To Predict the Lightfastness of Prints on Foil Applying Artificial Neural Network
  DOI :  10.2352/issn.2168-3204.2020.1.0.27  Published OnlineApril 2020

Archives, libraries, and commercial firms are utilizing new advanced imaging methods for research into cultural heritage objects. New technical systems, including the latest multispectral (MSI) and x-ray fluorescence (XRF) imaging systems and higher resolution cameras raise major challenges for not only the integration of new technologies, but also the ability to store, manage and access large amounts of data in archives and libraries. Recent advanced imaging of ancient Syriac palimpsests (parchment manuscripts with hidden texts embedded within them) demonstrated an approach that utilized multiple imaging techniques and integration and analysis of data from multiple sources. Three palimpsest imaging projects (Archimedes Palimpsest, Syriac Galen Palimpsest, HMML Palimpsest) supported research with a range of advanced imaging techniques with MSI and XRF, requiring implementation and standardization of new digitization and data management practices for the integration, preservation and sharing of advanced image data.

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Mahasweta Mandal, Swati Bandyopadhyay, "To Predict the Lightfastness of Prints on Foil Applying Artificial Neural Networkin Proc. IS&T Archiving 2020,  2020,  pp 27 - 32,

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