Developing the ArchAIDE Application: A digital workflow for identifying, organising and sharing archaeological pottery using automated image recognition

Pottery is of fundamental importance for understanding archaeological contexts, facilitating the understanding of production, trade flows, and social interactions. Pottery characterisation and the classification of ceramics is still a manual process, reliant on analogue catalogues created by special...

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Bibliographic Details
Main Authors: Francesca Anichini, Francesco Banterle, Jaume Buxeda i Garrigós, Marco Callieri, Nachum Dershowitz, Nevio Dubbini, Diego Lucendo Diaz, Tim Evans, Gabriele Gattiglia, Katie Green, Maria Letizia Gualandi, Miguel Angel Hervas, Barak Itkin, Marisol Madrid i Fernandez, Eva Miguel Gascón, Michael Remmy, Julian Richards, Roberto Scopigno, Llorenç Vila, Lior Wolf, Holly Wright, Massimo Zallocco
Format: Article
Language:English
Published: University of York 2020-03-01
Series:Internet Archaeology
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Online Access:https://intarch.ac.uk/journal/issue52/7/index.html
Description
Summary:Pottery is of fundamental importance for understanding archaeological contexts, facilitating the understanding of production, trade flows, and social interactions. Pottery characterisation and the classification of ceramics is still a manual process, reliant on analogue catalogues created by specialists, held in archives and libraries. The ArchAIDE project worked to streamline, optimise and economise the mundane aspects of these processes, using the latest automatic image recognition technology, while retaining key decision points necessary to create trusted results. Specifically, ArchAIDE worked to support classification and interpretation work (during both fieldwork and post-excavation analysis) with an innovative app for tablets and smartphones. This article summarises the work of this three-year project, funded by the European Union's Horizon 2020 Research and Innovation Programme under grant agreement N.693548, with a consortium of partners representing both the academic and industry-led ICT (Information and Communications Technology) domains, and the academic and development-led archaeology domains. The collaborative work of the archaeological and technical partners created a pipeline where potsherds are photographed, their characteristics compared against a trained neural network, and the results returned with suggested matches from a comparative collection with typical pottery types and characteristics. Once the correct type is identified, all relevant information for that type is linked to the new sherd and stored within a database that can be shared online. ArchAIDE integrated a variety of novel and best-practice approaches, both in the creation of the app, and the communication of the project to a range of stakeholders.
ISSN:1363-5387