Digital Applications in Archaeology and Cultural Heritage最新文献

This paper proposes a deep semantic binarization model, PLM-Res-U-Net, for enhancing palm-leaf manuscripts. PLM-Res-U-Net is a lightweight model comprising encoding and decoding blocks with skip connections. The model enhances the palm leaf manuscript by efficiently retaining the text strokes by removing the degradations such as uneven illumination, aging marks, brittleness, and background discolorations. Two datasets of palm leaf manuscript collections with multiple degradation patterns and diverse textured backgrounds are used for experimentation. PLM-Res-U-Net is trained from scratch with 50 epochs with a learning rate $of1e^{-8}$ with three sampling strategies. The performance of state-of-the-art deep learning models ResUnet, Pspnet, U-Net++, and Segnet are also evaluated along with two diverse benchmark datasets. Analysis shows that results obtained by the proposed PLM-Res-U-Net prove generalizability and computational efficacy with a dice score of 0.986. Additionally, PLM-Res-U-Net successfully preserves the edge strokes of the text compared with state-of-the-art models.

Qeydu Valley is a part of the Teymare region, which contains one the largest clusters of rock art in the central Iranian Plateau. Analyzing about 495 panels in more than 100 sites, this paper is intended to provide an insight into the landscape of rock art in Qeydu Valley. The paper explores the intersection of rock art positioning, movement patterns, and visual landscape in the study area. Total and cumulative viewshed, cost distance, and least-cost path analysis have been used to reconstruct the visibility dimension of the rock art locations in movement across the region. The total and cumulative viewshed analysis suggest that the panels showing a hunting theme benefit from a higher degree of visibility compared to the other petroglyphs.

The site B8b in Oslo, Norway, measured over 10,000 cubic metres and was excavated by the Norwegian Maritime Museum (NMM) and the Norwegian Institute for Cultural Heritage Research (NIKU) in 2022–2023. This paper presents the workflow for the 3D reconstruction of the stratigraphic phases on NMM's part of the site. The challenges that come with 3D reconstructing a site of this size are discussed and compared to other sites where 3D stratigraphic reconstruction has been attempted. For this study, solid meshes of the stratigraphy were created in Blender, then integrated with other excavation data in ArcGIS PRO. The 3D dataset of the stratigraphy was subsequently used for analysing the inclination of the former seafloor and the relationship between the site's stratigraphy and finds such as a late medieval boat wreck.

The Old City of Aleppo suffered extensive urban damage during the war in Syria. This study showcases the implementation of digital pipelines in visualizing and studying the history and evolution of two districts within the Old City. The aim of this study was to develop a parametric workflow that would allow for the reconstruction of a section of Mamluk Aleppo. This reconstruction was based on both cartographical and historical inputs. A comprehensive digital field survey was conducted using laser scanning and aerial photogrammetry techniques. The resulting point cloud data is then compared to the historical parametric model, and 3D urban changes to the studied area were identified.

In the Maramureș region of Romania there is a large number of historic wooden churches dating back to the 17th and 18th centuries. These objects of tangible cultural heritage continue to be exposed to degradation factors. Meanwhile, their interiors hide important and historically valuable artefacts of cultural heritage. Their loss would noticeably impoverish the heritage of local communities. This article presents the problems of 3D scanning the interiors of wooden historic churches, the scanning methodology specifically developed for this occasion, the equipment used and its parameters, and the results of its application. Four examples of wooden churches from the Maramureș region were studied: modern laser scanning technologies with appropriate selection of parameters permits a satisfactorily precise scan of the interior of a wooden religious building, even in difficult lighting conditions. The methodology and equipment choice was proven to be successful and is recommended here for future projects in the region and for structures facing similar challenges.

The search for predictive models in archaeology using geographical data and artificial intelligence (AI) has made progress, but there is a scarcity of studies focusing on South America. Serranópolis, in Goiás, Central-West Brazil, emerges as an ideal landscapefor applying AI and geographical data to predict archaeological sites. This study aimed to predict potential archaeological locations in Serranópolis using topographic variables and four supervised classification algorithms: C5.0, Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and Gradient Boosting Machine (GBM). The methodology involved sample points representing open-air archaeological sites and rock shelters, along with randomly selected pseudo-absence samples. Eighteen topographic variables from a digital elevation model were considered. RF outperformed other algorithms, producing a probability map of site occurrence. Key predictors included sky view factor, roughness, topographic depression, and slope. The findings enhance our understanding of archaeological potential in this region, highlighting the effectiveness of RF in predictive modeling.

A digital 3D model of the Ma'agan Mikhael B ship was developed by resourcing excavation data, iconographic representations, and relevant documentation. A computer-aided design system was used to digitally replicate the ship, also yielding 3D prints used to refine the results. The digital model also served to test amphora cargo loading scenarios, considering maritime dictates of ship stability, accessibility, and commerce. A standard maritime-engineering analysis of stability and strength, and computational fluid dynamics analyses were performed on the digital model to evaluate hull resistance and the power of the ship's lateen sail. The simulations demonstrated that the fully loaded merchantman was seaworthy and made satisfactory speed over ground.

The management of cultural heritage leads to the creation of digital files that contain representations of cultural heritage elements. Over the last few decades, a number of technologies designed for creating 3D models of objects or scenes have been developed, and the number of digitisation platforms has increased. Despite the dissemination of 3D models on these platforms, generally, the methodologies used appears to be undocumented and there is a lack of standards for providing metadata for creating 3D models. In this paper, a metadata schema for 3D models of archaeological objects is proposed, addressing the possible techniques used to create and process such models and considering that not all digital objects are the same, as they are produced in different ways and with different metrics and chromatic accuracies. Additionally, a core of the most crucial components is suggested to alleviate the difficulty of producing exhaustive metadata to represent the entire procedure.

In Ancient Greece, architecture and sculpture were painted. Nevertheless, the exact appearance of the colours used to decorate buildings remains largely unknown due to lack of evidence. The Temple of Apollo at Delphi, is no exception to this process. Since its discovery in 1894, the question of polychromy has been partially studied. This situation can be explained by the difficulty of detecting colours traces directly on the ancient blocks by simple visual observation. The majority of them are imperceptible to the naked eye. This paper aims to put a exploratory methodology based on archaeometric, photogrammetric and computer analyses in order to the locate, characterize traces of polychromy that are invisible to the naked eye and to provide new data that can be used to reconstruct the architectural polychromy of the Temple of Apollo at Delphi in the late classical period.

Motivated by the need to leverage technologies to enhance the preservation, accessibility, quantitative data analysis, and valorization of Dance Heritage, this work introduces DanXe, a framework based on Artificial Intelligence and Extended Reality for the digitization, automatic analysis, and immersive manipulations of tangible and intangible cultural heritage material. Our contribution offers a framework to define the Digital Twin of documentary assets associated with dance heritage, enriching the storytelling of its traditions, performers, and specific languages. The implications of the proposed framework extend beyond the realm of dance, impacting various creative industries and cultural heritage preservation efforts. The approach is validated through a specific case study, linked to the artistic legacy of the dancer and choreographer Rudolf Nureyev intending to narrate his artistic impact. Moreover, we contribute with the description of an effective strategy for the comprehensive organization and analysis of all materials related to the legacy of the dancer.