Computational Approaches

Computational approaches have revolutionised the field of manuscript research by enabling the analysis of vast amounts of data from digitised manuscripts. Machine learning and pattern recognition have been particularly useful in this regard, as they can assist in the automatic identification and classification of images and text within the manuscripts. With the help of these techniques, scholars can uncover new insights into the historical context, production, and provenance of manuscripts. Moreover, the analysis of data from advanced acquisition techniques, such as multispectral imaging, X-ray fluorescence and infrared spectroscopy, has also proved to be valuable in revealing hidden features of the manuscripts, such as erased or overwritten text, and identifying the materials used in their production. As such, computational approaches have become an indispensable tool for manuscript researchers, allowing them to delve deeper into the intricacies of these fascinating historical artefacts.