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Volume: 34 | Article ID: MOBMU-362
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Recognition of objects from looted excavations by smartphone app and deep learning
  DOI :  10.2352/EI.2022.34.3.MOBMU-362  Published OnlineJanuary 2022
Abstract
Abstract

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.

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Waldemar Berchtold, Huajian Liu, Simon Bugert, York Yannikos, Jingcun Wang, Julian Heeger, Martin Steinebach, Marco Frühwein, "Recognition of objects from looted excavations by smartphone app and deep learningin Proc. IS&T Int’l. Symp. on Electronic Imaging: Mobile Devices and Multimedia: Enabling Technologies, Algorithms, and Applications,  2022,  pp 362-1 - 362-4,  https://doi.org/10.2352/EI.2022.34.3.MOBMU-362

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