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Automated Detection of Hillforts in Remote Sensing Imagery With Deep Multimodal...
Canedo, Daniel; Fonte, João; Dias, Rita; do Pereiro, Tiago; Gonçalves-Seco, Luís; Vázquez, Marta; Georgieva, Petia; Neves, António J RRecent advancements in remote sensing and artificial intelligence can potentially revolutionize the automated detection of archaeological sites. However, the challenging task of interpreting remote sensing imagery combined with the intricate shapes of archaeological sites can hinder the performance of computer vision systems. This work presents a computer vision system trained for efficient hillfort detection i...
The Synergy between artificial intelligence, remote sensing, and archaeological...
Canedo, Daniel; Hipólito, João; Fonte, João; Dias, Rita; Pereiro, Tiago do; Georgieva, Petia; Gonçalves-Seco, Luís; Vázquez, Marta; Pires, NelsonThe increasing relevance of remote sensing and artificial intelligence (AI) for archaeological research and cultural heritage management is undeniable. However, there is a critical gap in this field. Many studies conclude with identifying hundreds or even thousands of potential sites, but very few follow through with crucial fieldwork validation to confirm their existence. This research addresses this gap by pr...
Automated detection of hillforts in remote sensing imagery with deep multimodal...
Canedo, Daniel; Fonte, João; Dias, Rita; Pereiro, Tiago do; Gonçalves‐Seco, Luís; Vázquez, Marta; Georgieva, Petia; Neves, António J. R.Recent advancements in remote sensing and artificial intelligence can potentially revolutionize the automated detection of archaeological sites. However, the challenging task of interpreting remote sensing imagery combined with the intricate shapes of archaeological sites can hinder the performance of computer vision systems. This work presents a computer vision system trained for efficient hillfort detection i...
Uncovering archaeological sites in airborne LiDAR data with data-centric artifi...
Canedo, Daniel; Fonte, João; Seco, Luis Gonçalves; Vázquez, Marta; Dias, Rita; Pereiro, Tiago do; Hipólito, João; Menéndez-Marsh, FernandoMapping potential archaeological sites using remote sensing and artificial intelligence can be an efficient tool to assist archaeologists during project planning and fieldwork. This paper explores the use of airborne LiDAR data and data-centric artificial intelligence for identifying potential burial mounds. The challenge of exploring the landscape and mapping new archaeological sites, coupled with the difficul...