Changing attitudes: lessons for countering the trafficking of cultural objects

Runhovde, Siv Rebekka

doi:10.1080/17440572.2022.2117697

Cited by 1 publication

(1 citation statement)

References 47 publications

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“…Among various international treaties, an important one is the UNESCO 1970 Convention on the Means of Prohibiting and Preventing the Illicit Import, Export and Transfer of Ownership of Cultural Property treaty, which was intended to help limit the sale of illegally obtained heritage objects and thereby potentially limiting damage to heritage sites where cultural objects come from (UNESCO 2022). While over 140 countries have now ratified this international treaty, enforcement and attitudes towards enforcing this and other similar treaties have been argued to be weak, including in relative priorities for law enforcement (Runhovde 2022). This potentially necessitates more time efficient tools that demand less resources to aid law enforcement, particularly if the priority in allocating financial and personnel resources in preventing looting or illicit removal of cultural objects from sites is likely to remain low in the future.…”

Section: Looting Of Heritage Sitesmentioning

confidence: 99%

Monitoring Looting at Cultural Heritage Sites: Applying Deep Learning on Optical Unmanned Aerial Vehicles Data as a Solution

Altaweel,

Khelifi,

Shana’ah

2023

Social Science Computer Review

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The looting of cultural heritage sites has been a growing problem and threatens national economies, social identity, destroys research potential, and traumatizes communities. For many countries, the challenge in protecting heritage is that there are often too few resources, particularly paid site guards, while sites can also be in remote locations. Here, we develop a new approach that applies deep learning methods to detect the presence of looting at heritage sites using optical imagery from unmanned aerial vehicles (UAVs). We present results that demonstrate the accuracy, precision, and recall of our approach. Results show that optical UAV data can be an easy way for authorities to monitor heritage sites, demonstrating the utility of deep learning in aiding the protection of heritage sites by automating the detection of any new damage to sites. We discuss the impact and potential for deep learning to be used as a tool for the protection of heritage sites. How the approach could be improved with new data is also discussed. Additionally, the code and data used are provided as part of the outputs.

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Section: Looting Of Heritage Sitesmentioning

confidence: 99%