Publikationen

Autor	Berchtold, Waldemar; Liu, Huajian; Bugert, Simon; Yannikos, York; Wang, Jingcun; Heeger, Julian; Steinebach, Martin; Frühwein, Marco
Datum	2022
Art	Journal Article
Abstrakt	In 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.
Konferenz	Conference "Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications" 2022
Url	https://publica.fraunhofer.de/handle/publica/414472

Recognition of objects from looted excavations by smartphone app and deep learning