Difference between revisions of "Reconsidering the Roman Workshop"

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<p>Building upon the work of Richard Grasby amongst others, this pilot project will develop a machine learning model to locate and extract characters and make a series of measurements to investigate the extent to which Roman workshops made use of specific controlling ‘modules’ in the creation of inscribed texts. By combining machine learning with traditional epigraphic methods the project aims to deepen our understanding of Roman drafting and lettercutting processes.</p>
<p>Building upon the work of Richard Grasby amongst others, this pilot project will develop a machine learning model to locate and extract characters and make a series of measurements to investigate the extent to which Roman workshops made use of specific controlling ‘modules’ in the creation of inscribed texts. By combining machine learning with traditional epigraphic methods the project aims to deepen our understanding of Roman drafting and lettercutting processes.</p>
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==References==
* Charlotte Tupman (2020), "Reconsidering the Roman workshop: Applying machine learning to the study of inscribing texts". ''Digital Classicist London Seminar'' 2020-08-07. Available: https://www.youtube.com/watch?v=sVUg9R13l5E


[[category:Projects]]
[[category:Projects]]
[[category:Epigraphy]]
[[category:Epigraphy]]
[[category:Machine learning]]
[[category:Machine learning]]

Latest revision as of 11:27, 5 August 2021

Available

Directors

  • Charlotte Tupman
  • Jacq Christmas

Description

Taken from the University of Exeter project announcement (accessed 2021-08-05):

Charlotte Tupman (Classics & Ancient History/Digital Humanities) and Jacq Christmas (Computer Science) hold an Institute for Data Science and Artificial Intelligence Research Award for a 6-month pilot project called Reconsidering the Roman Workshop, which will develop a machine learning model to conduct a large-scale analysis of the planning processes involved in creating Latin inscriptions. Dmitry Kangin, Research Fellow in Computer Science, will work with Charlotte and Jacq to apply neural networks to analyse a subset of almost 40,000 images of inscribed texts that have been made available by the Epigraphische Datenbank Heidelberg. As part of his work Kangin will develop a new basis for training Neural ODEs (Ordinary Differential Equations).

Building upon the work of Richard Grasby amongst others, this pilot project will develop a machine learning model to locate and extract characters and make a series of measurements to investigate the extent to which Roman workshops made use of specific controlling ‘modules’ in the creation of inscribed texts. By combining machine learning with traditional epigraphic methods the project aims to deepen our understanding of Roman drafting and lettercutting processes.

References

  • Charlotte Tupman (2020), "Reconsidering the Roman workshop: Applying machine learning to the study of inscribing texts". Digital Classicist London Seminar 2020-08-07. Available: https://www.youtube.com/watch?v=sVUg9R13l5E