Automatic identification of Dong Son antique glass artifacts using evolving learning

Abstract

Regarding the Dong Son culture, given the diverse range of artifacts discovered, we propose the utilization of an artificial intelligence system for the automated and comprehensive identification of Dong Son glass jewelry through SEM gemological analysis. This approach, which has gained prominence in the field of archaeology worldwide over the past five years, aims to integrate advanced technology into Vietnamese archaeology. Our research is motivated by the unique conditions present in archaeology, where we seek to employ evolving learning algorithms to archaeological databases, comparing and selecting the most suitable model that aligns with the archeological dataset's performance. We have developed the Recognition Automatic System for Dong Son Antique Glasses (RAS-DSA), capable of accurately distinguishing between Dong Son and non-Dong Son glass ornaments, and is freely distributed to experts and archaeologists. This collaborative research involves Nam Can Tho University, Hanoi University of Mining and Geology, the Vietnamese Institute of Archaeology, and the UNESCO Center for Research and Conservation of Vietnamese Antiquities.