Automatic identification of Dong Son antique glass artifacts using evolving learning

Anh-Khoi Ngo-Ho, Hoang-Bac Bui, Van-Trieu Pham
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引用次数: 1

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.
基于演化学习的东孙古董玻璃文物自动识别
关于东山文化,鉴于发现的文物种类繁多,我们建议利用人工智能系统通过扫描电镜宝石学分析对东山玻璃珠宝进行自动化和全面的识别。这种方法在过去五年中在世界考古领域获得了突出的地位,旨在将先进技术融入越南考古学。我们的研究是由考古学中存在的独特条件所驱动的,我们试图将不断发展的学习算法应用于考古数据库,比较并选择与考古数据集性能一致的最合适的模型。我们开发了能够准确区分东山和非东山玻璃饰品的东山古董玻璃识别自动系统(RAS-DSA),并免费分发给专家和考古学家。这项合作研究包括南芹苴大学、河内矿业和地质大学、越南考古研究所和联合国教科文组织越南古物研究和保护中心。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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