Ex Machina: Machine Learning, ceramics & rock art in the Khorat Plateau, Thailand
Goldfinch, Felise, Chang, Nigel, and Hardy, Dianna (2024) Ex Machina: Machine Learning, ceramics & rock art in the Khorat Plateau, Thailand. SPAFA Journal. (In Press)
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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.
Item ID: | 79346 |
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Item Type: | Article (Research - C1) |
ISSN: | 2586-8721 |
Copyright Information: | Authors who publish with this journal retain copyright and grant SEAMEO SPAFA right of first publication with the work simultaneously licensed under a Creative Commons 4.0 Attribution Non Commercial-No Derivatives License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal. Authors grant SEAMEO SPAFA the right to use images and multimedia for non-commercial purposes (e.g. in SPAFA publications). |
Projects and Grants: | The National Research Council of Thailand and the Thai Fine Arts Department and the kind cooperation of the BNW community |
Date Deposited: | 20 Jul 2023 01:57 |
FoR Codes: | 43 HISTORY, HERITAGE AND ARCHAEOLOGY > 4301 Archaeology > 430102 Archaeology of Asia, Africa and the Americas @ 50% 46 INFORMATION AND COMPUTING SCIENCES > 4611 Machine learning > 461104 Neural networks @ 50% |
SEO Codes: | 13 CULTURE AND SOCIETY > 1307 Understanding past societies > 130702 Understanding Asia’s past @ 50% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280113 Expanding knowledge in history, heritage and archaeology @ 25% 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 25% |
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