Developing Usable Datasets for AI training: Real and simulated sherds

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Abstract
This article discusses the process for creating a dataset to train and test the core and the corrector AI classifiers of the Arch-I-Scan Project. This dataset includes the photographs of real sherds that were compiled by the project from the collections of our project partners as well as synthetic sherds that were generated to supplement the low numbers of real sherd training data and to account for the imbalances among the numbers of real sherds per class (i.e., per vessel form). This article presents the simulation process used to create the synthetic sherds, as well as the process we used to decrease the differences between images of real and simulated sherds so that they were useable together for training the machine. Finally, the compilation and size of the resulting overall dataset are outlined.

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