Creating a Ceramic Typology Using Machine Learning: A Case Study from the Middle Bronze Age South Caucasus

This thesis explores the possibility of using machine learning image recognition and computational clustering to create new ceramic typologies using painted pottery artefacts from the Middle Bronze Age South Caucasus. The methodology used in this case study aims to highlight patterns in the way decorative motifs on painted pottery appear together on ceramic vessels.