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Author (up) Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero edit  url
doi  openurl
  Title Recurrent Comparator with attention models to detect counterfeit documents Type Conference Article
  Year 2019 Publication 15th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages  
  Abstract This paper is focused on the detection of counterfeit documents via the recurrent comparison of the security textured background regions of two images. The main contributions are twofold: first we apply and adapt a recurrent comparator architecture with attention mechanism to the counterfeit detection task, which constructs a representation of the background regions by recurrently condition the next observation, learning the difference between genuine and counterfeit images through iterative glimpses. Second we propose a new counterfeit document dataset to ensure the generalization of the learned model towards the detection of the lack of resolution during the counterfeit manufacturing. The presented network, outperforms state-of-the-art classification approaches for counterfeit detection as demonstrated in the evaluation.  
  Address Sidney; Australia; September 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.140; 600.121; 601.269 Approved no  
  Call Number Admin @ si @ BRL2019 Serial 3456  
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