Publicação
Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies
| datacite.subject.sdg | 09:Indústria, Inovação e Infraestruturas | |
| datacite.subject.sdg | 11:Cidades e Comunidades Sustentáveis | |
| datacite.subject.sdg | 04:Educação de Qualidade | |
| dc.contributor.author | Santos, Joel | |
| dc.contributor.author | Nunes, Diogo A.P. | |
| dc.contributor.author | Padnevych, Ruslan | |
| dc.contributor.author | Quaresma, José Carlos | |
| dc.contributor.author | Lopes, Martim | |
| dc.contributor.author | Gil, Joana | |
| dc.contributor.author | BERNARDES, João Pedro | |
| dc.contributor.author | Casimiro, Tania Manuel | |
| dc.date.accessioned | 2026-05-14T13:24:25Z | |
| dc.date.available | 2026-05-14T13:24:25Z | |
| dc.date.issued | 2024-05-15 | |
| dc.description.abstract | This article presents a novel approach to classifying archaeological artefacts using machine learning, specifically deep learning, rather than relying on traditional, time-consuming human-based methods. By employing Convolutional Neural Networks (CNNs), this approach aims to expedite and enhance the identification process, making it more accessible to a wider audience. The study focuses on two types of artefacts- Roman Lusitanian amphorae (2nd-5th centuries) and Portuguese faience (16th-18th centuries)- chosen for their diversity. While Lusitanian amphorae lack decoration, Portuguese faience poses challenges with subtle colour variations. The study demonstrates the potential of this approach to overcome these hurdles. The paper outlines the methodology, dataset creation, and model training, emphasizing the importance of extensive data and computational resources. The ultimate objective of this research is to develop a mobile application that utilizes image classification techniques to accurately classify ceramic sherds and bring about a significant transformation in archaeological classification. | eng |
| dc.identifier.doi | 10.1080/20548923.2024.2343214 | |
| dc.identifier.issn | 2054-8923 | |
| dc.identifier.uri | http://hdl.handle.net/10400.1/28965 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | Informa | |
| dc.relation.ispartof | STAR: Science & Technology of Archaeological Research | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Deep learning | |
| dc.subject | Machine learning | |
| dc.subject | Artificial intelligence | |
| dc.subject | Amphorae | |
| dc.subject | Faience | |
| dc.subject | Ceramic identification | |
| dc.title | Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies | eng |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.issue | 1 | |
| oaire.citation.title | STAR: SCIENCE & TECHNOLOGY OF ARCHAEOLOGICAL RESEARCH | |
| oaire.citation.volume | 10 | |
| oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
| person.familyName | BERNARDES | |
| person.givenName | João Pedro | |
| person.identifier.ciencia-id | 4B12-1CB7-C689 | |
| person.identifier.orcid | 0000-0002-1086-2128 | |
| person.identifier.rid | T-6479-2017 | |
| person.identifier.scopus-author-id | 56090302700 | |
| relation.isAuthorOfPublication | c75c0ff0-c6b9-4994-8fd4-72c90f3ff92e | |
| relation.isAuthorOfPublication.latestForDiscovery | c75c0ff0-c6b9-4994-8fd4-72c90f3ff92e |
Ficheiros
Principais
1 - 1 de 1
A carregar...
- Nome:
- Automatic ceramic identification using machine learning. Lusitanian amphorae and Faience. Two Portuguese case studies.pdf
- Tamanho:
- 2.24 MB
- Formato:
- Adobe Portable Document Format
Licença
1 - 1 de 1
Miniatura indisponível
- Nome:
- license.txt
- Tamanho:
- 3.46 KB
- Formato:
- Item-specific license agreed upon to submission
- Descrição: