Berchtold, WaldemarWaldemarBerchtoldLiu, HuajianHuajianLiuBugert, SimonSimonBugertYannikos, YorkYorkYannikosWang, JingcunJingcunWangHeeger, JulianJulianHeegerSteinebach, MartinMartinSteinebachFrühwein, MarcoMarcoFrühwein2022-04-282022-04-282022-01https://publica.fraunhofer.de/handle/publica/41447210.2352/EI.2022.34.3.MOBMU-362In this paper, we present a development for recognizing objects from looted excavations. Experts with an archaeological background are not always available where an object needs to be assessed for tradability. For this purpose, we developed a smartphone app that can provide on-site assistance in the initial assessment of archaeological objects. The app sends captured images to a server for recognition and receives results with similar objects and their metadata along with an associated probability. A user can thus use these information to infer the provenance of the photographed object. To this end, a classifier was trained using a transfer learning procedure and the features of the trained network were used for an image matching procedure. The developed application will be tested by law enforcement agencies with a total of 15 smartphones for six months starting in early October.enlooted excavationsmartphone appimage matchingjournal article