Ex Machina: Machine Learning, ceramics & rock art in the Khorat Plateau, Thailand

Goldfinch, Felise;Chang, Nigel;Hardy, Dianna

Abstract

Machine Learning for the recognition and analysis of prehistoric rock art and pottery is a promising area of research that could reveal new insights into cultural heritage and identity. Deep Learning (a form of Artificial Intelligence) can now be used to train powerful models to automatically recognise pottery and rock art images, overcoming resource constraints such as time, manpower, and lack of funding. This article provides a preliminary overview and proof of concept by providing Machine Learning approaches based on current advancements in Deep Learning to train a model to recognise images of pottery and prehistoric rock art. These methods can process large amounts of data quickly and accurately, revealing new patterns and relationships. Although ML can be a complex undertaking, new tools make it accessible to the archaeological practitioner who is not an AI expert.

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SPAFA Journal

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SPAFA Journal

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2586-8721

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Southeast Asian Ministers of Education Organization

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