Supervised Models to Support Investigations of Ancient Coins

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
} }
Citation