Abstract

Detecting surface potsherds using low-altitude remote sensing is challenging due to severe class imbalance and limited training data. This study develops and validates a semi-automatic detection methodology that adapts threshold-optimized boosting classifiers (AdaBoost, XGBoost) to maximize ceramic detection recall under extreme class imbalance in the Western Megaris archeological landscape, Greece. Models were trained on only 15% of the available data to simulate realistic field conditions. Evaluation emphasized recall-oriented metrics (precision, recall, F1-score, AUC) for the minority class, addressing the accuracy paradox where high overall accuracy masks poor rare-class performance. Threshold optimization enabled AdaBoost and XGBoost to achieve substantially improved recall compared to baseline methods, with detection-to-ground-truth ratios of 2.5 and 3.2, respectively, reflecting deliberate prioritization of recall over precision for exploratory survey purposes. The results demonstrate that this methodological framework provides archeologically interpretable screening tools for identifying high-probability ceramic locations, supporting more efficient field survey design and heritage documentation workflows in Mediterranean landscapes.

Argyrou, A.; Fasson, F.; Farinetti, E.; Papakonstantinou, A.; Alexakis, D.D.; Agapiou, A. Learning from the Rare: Overcoming Class Imbalance in Archaeological Object Detection with Boosting Methods. Heritage 2026, 9, 99. https://doi.org/10.3390/heritage9030099

The presentation took place on 11 and 12 February 2026, at the premises of the Laboratory of Spatial Analysis, GIS and Thematic Mapping, where the CONNECTING project was presented to postgraduate students and research staff. The lecture provided a comprehensive overview of the project, with particular emphasis on the technological architecture of the Cloud Data Centre. It also highlighted the methodologies applied for the management and visualization of 2D and 3D geospatial datasets, as well as the rationale behind key system design decisions, including aspects of data security, interoperability, and performance optimization—especially in relation to sensitive cultural heritage geospatial information relevant to spatial planning and regional development.

The session contributed significantly to the enhancement of participants’ knowledge and fostered constructive academic exchange on emerging approaches in geospatial data management and cultural heritage preservation.

Abstract:  Chatbots have emerged as a promising interface for facilitating access to complex datasets, allowing users to pose questions in natural language rather than relying on specialized technical workflows. At the same time, remote sensing has transformed archaeological practice by producing vast amounts of imagery from LiDAR, drones, and satellites. While these advances have created unprecedented opportunities for discovery, they also pose significant challenges due to the scale, heterogeneity, and interpretative demands of the data. In related scientific domains, multimodal conversational systems capable of integrating natural language interaction with image-based analysis have advanced rapidly, supported by a growing body of survey and review literature documenting their architectures, datasets, and applications across multiple fields. By contrast, archaeological applications of chatbots remain limited to text-based prototypes, primarily focused on education, cultural heritage mediation or archival search. This review synthesizes the historical development of chatbots, examines their current use in remote sensing, and evaluates the barriers to adapting such systems for archaeology. Four major challenges are identified: data scale and heterogeneity, scarcity of training datasets, computational costs, and uncertainties around usability and adoption. By comparing experiences across domains, this review highlights both the opportunities and the limitations of integrating conversational AI into archaeological workflows. The central conclusion is that domain-specific adaptation is essential if multimodal chatbots are to become effective analytical partners in archaeology.

Melillos, N.; Agapiou, A. AI Chatbots and Remote Sensing Archaeology: Current Landscape, Technical Barriers, and Future Directions. Heritage 2026, 9, 32. https://doi.org/10.3390/heritage9010032

The discussions focused on a consolidated review of the project’s overall progress as it approaches its completion in May 2026. Particular emphasis was placed on completed deliverables and finalised activities, alongside a brief overview of the few remaining actions required for the successful closure of the project. Updates were also provided on the status of equipment, infrastructure implementation, and administrative procedures at both CUT and UCY, noting that the majority of these components have now been completed.

In addition, the meeting addressed the outcomes of demonstration activities, which have largely been concluded, and reflected on their contribution to the project’s objectives. The meeting served as a key moment to ensure final alignment across Work Packages, reinforce collaboration among consortium members, and coordinate the remaining steps toward project completion. As the CONNECTING project enters its final phase, the consortium reaffirmed its commitment to timely execution, knowledge transfer, and maximising the project’s lasting impact.

The awarded project, presented by Mr. Petros Artemi, is titled:

“Preservation and Promotion of the Cultural Heritage of the Municipality of Kyrenia through a Web-Based Geographic Information System (GIS)”
Authors: Petros Artemi, Marios Zervas, Kyriakos Michaelides, Apostolos Papakonstantinou, Athos Agapiou, G. Lazaros Kotsikas, Theodoros Lafazanis, Fotos Loukas, Ioanna Fouroukla.

The project involves the design and development of an online GIS application that highlights the rich cultural heritage of the Municipality of Kyrenia, offering historical information, maps, and audiovisual material from the 19th century to the present day.

This collaborative effort was made possible through the contribution of:
🔹 The Cultural Heritage & Earth Observation Laboratory (EOcult)
🔹 The Cartography & Geovisualization Laboratory (CartoGiLab)
of the Department of Civil Engineering & Geoinformatics Engineering, CUT,
in partnership with the University Library and the Municipality of Kyrenia.

The multimedia content has been sourced and developed from the Athena and Apsida repositories.

We are especially proud that members of the CONNECTING project team, Project Coordinator Dr. Athos Agapiou, Dr. Apostolos Papakonstantinou, and Kyriakos Michaelides contributed actively to the development and support of this application, further strengthening our joint efforts to preserve and promote cultural heritage through innovative digital tools.

✨ A big congratulations to the entire team for this important recognition!
Let’s continue working together to advance digital cultural heritage and strengthen collaborative initiatives.

Find out more about: https://www.euromed-dch.eu/