No abstract

No abstract

No abstract

No abstract

In the last ten years, artificial intelligence (AI) techniques have been applied in archaeology. The ArchAIDE project realised an AI-based application to recognise archaeological pottery. Pottery is of paramount importance for understanding archaeological contexts. However, recognition of ceramics is still a manual, time-consuming activity, reliant on analogue catalogues. The project developed two complementary machine-learning tools to propose identifications based on images captured on-site, for optimising and economising this process, while retaining key decision points necessary to create trusted results. One method relies on the shape of a potsherd; the other is based on decorative features. For the shape-based recognition, a novel deep-learning architecture was employed, integrating shape information from points along the inner and outer profile of a sherd. The decoration classifier is based on relatively standard architectures used in image recognition. In both cases, training the algorithms meant facing challenges related to real-world archaeological data: the scarcity of labelled data; extreme imbalance between instances of different categories; and the need to take note of minute differentiating features. Finally, the creation of a desktop and mobile application that integrates the AI classifiers provides an easy-to-use interface for pottery classification and storing pottery data.

Hyperspectral imaging is a widespread non-destructive analytical technique used in various disciplines for highlighting invisible patterns and mapping the spectral signatures of selected targets. In archaeology, it has been mostly applied for remote sensing satellite imagery to disclose information about features that are hidden undergrounds. Targeted applications of hyperspectral imaging have been developed in the last few years, opening up new perspectives for material analysis based on spectral mapping. Recent advances in portable instrumentation have led to the development of small and rugged cameras that can be used directly in the field for investigating different targets. This paper discusses the use of a small ultraportable hyperspectral camera in the VIS-NIR range for archaeological fieldwork with regards to hardware, data processing workflows, and spectral information that can be used for the better planning of research and for in situ screening.

No abstract

No abstract