| Summary: | This paper describes the preliminary results of an ancient history and computer science collaboration to apply machine learning to the identification of text within images of inscriptions, one of our major sources of evidence for the Roman world. This work contributes to our understanding of their planning processes. We describe a machine learning method for locating text within several thousand images, and discuss the next steps for establishing the extent to which Roman workshops used specific controlling modules in the creation of inscriptions. The aims are twofold: to improve our knowledge of Roman monumental practices and craftsmanship, and to enable accurate restorations of damaged texts through a more comprehensive understanding of how they were planned and executed.
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