{"id":10933,"date":"2025-10-30T18:57:45","date_gmt":"2025-10-30T17:57:45","guid":{"rendered":"https:\/\/eurocc.nscc.sk\/?p=10933"},"modified":"2025-10-30T19:02:04","modified_gmt":"2025-10-30T18:02:04","slug":"archeologia-pohanana-umelou-inteligenciou-s-llm-detekcia-archeologickych-lokalit-z-leteckych-snimok","status":"publish","type":"post","link":"https:\/\/eurocc.nscc.sk\/en\/archeologia-pohanana-umelou-inteligenciou-s-llm-detekcia-archeologickych-lokalit-z-leteckych-snimok\/","title":{"rendered":"AI-Driven Archaeology with LLMs \u2014 Detecting Archaeological Sites from Aerial Imagery<\/strong>"},"content":{"rendered":"
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AI-Driven Archaeology with LLMs \u2014 Detecting Archaeological Sites from Aerial Imagery<\/strong><\/h5>\n\n\n\n

Discover how artificial intelligence and large language models are redefining the way we uncover traces of the past.<\/strong>

This webinar will explore how advanced AI techniques, inspired by LLMs, can analyse aerial and LiDAR imagery to detect archaeological sites with unprecedented precision. Dr. Daniel Canedo from the University of Aveiro will present real-world use cases where Vision Transformers and multimodal learning reveal hidden patterns in the landscape \u2014 bridging technology and cultural heritage.<\/p>\n\n\n\n

Date and Time:<\/strong>
Tuesday, November 18th, 2025 | 10:00 AM CEST (9:00 PT)
Online | Free Registration<\/p>\n\n\n\n

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REGISTRATION<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n
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This webinar is organized by the Slovak National Supercomputing Centre<\/strong> as part of the EuroCC project (National Competence Centre \u2013 NCC Slovakia<\/a><\/strong>) in cooperation with NCC Portugal<\/strong> , within the LLM Webinar Series connecting high-performance computing with artificial intelligence, culture, and innovation. The webinar will be held in English.<\/p>\n\n\n\n

The webinar will be held in English.<\/p>\n\n\n\n

Abstract:<\/strong><\/p>\n\n\n\n

Archaeological site detection is entering a new era thanks to advances in remote sensing and artificial intelligence. Archaeological sites such as hillforts often have irregular and complex shapes, making them difficult to identify using conventional computer-vision methods. Multimodal approaches that combine LiDAR-derived LRM images with aerial orthoimagery improve detection accuracy, but false positives remain a major challenge.<\/p>\n\n\n\n

This presentation explores how Vision Transformers and LLM-inspired architectures can address these limitations. By using cross-modal attention mechanisms, these models integrate multiple data sources to enable precise boundary detection, reduced false positives, and scalable application across diverse landscapes and site types. A key element of this workflow is a human-in-the-loop refinement process, in which archaeologists review and provide feedback on model predictions. This iterative collaboration enriches the training data, enhances the model\u2019s ability to distinguish true sites from background anomalies, and increases overall detection reliability.<\/p>\n\n\n\n

Results from Northwest Iberia show a 99.3% reduction in false positives after a single refinement cycle, while nationwide deployment in England demonstrates robust performance across varied site morphologies. Combining multimodal fusion, transformer-based architectures, and expert-guided refinement, this approach delivers both accuracy and interpretability. The talk will conclude with insights into predictive modelling for identifying high-potential areas, accelerating large-scale archaeological surveys, and improving efficiency in heritage mapping.<\/p>\n\n\n\n

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Speaker:<\/strong><\/p>\n\n\n\n

Dr. Daniel Canedo<\/strong> \u2013 <\/strong>Research Fellow, Institute of Electronics and Informatics Engineering of Aveiro, University of Aveiro<\/p>\n\n\n\n

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Dr. Daniel Canedo received his Ph.D. in Computer Engineering from the University of Aveiro, Portugal, in 2024. Since 2017, he has been a Research Fellow with the Institute of Electronics and Informatics Engineering of Aveiro (IEETA). His research interests include computer vision and artificial intelligence, with a particular focus on their applications to complex pattern detection and image-based reasoning.<\/p>\n\n\n\n

He has published in several international journals and conference proceedings and was awarded first place in the NATO StratCom Competition \u201eHow to detect malicious use of video and\/or photographic content online\u201d<\/em> (December 2018, Riga, Latvia).<\/p>\n\n\n\n

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Topics Include:<\/strong><\/p>\n\n\n\n