Supervised Models to Support Investigations of Ancient Coins
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
This paper presents the initial findings of the ongoing MML-ARCH project, which uses machine learning (ML) algorithms to create predictive, supervised models for analyzing archaeological, numismatic and physicochemical data. Specifically, the study proposes using convolutional neural network (CNN) algorithms to predict the minting year of ancient Roman Republican coins based on the iconography on the obverse and reverse.
Description
CCS Concepts: Computing methodologies → Supervised learning by regression; Applied computing → Archaeology
@inproceedings{10.2312:dh.20253153,
booktitle = {Digital Heritage},
editor = {Campana, Stefano and Ferdani, Daniele and Graf, Holger and Guidi, Gabriele and Hegarty, Zackary and Pescarin, Sofia and Remondino, Fabio},
title = {{Supervised Models to Support Investigations of Ancient Coins}},
author = {Naso, Luca and Sole, Lavinia and Patti, Andrea and Armetta, Francesco and Celso, Fabrizio Lo and Patatu, Wladimiro Carlo and Saladino, Maria Luisa},
year = {2025},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-277-6},
DOI = {10.2312/dh.20253153}
}