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Author (up) Albert Berenguel; Oriol Ramos Terrades; Josep Llados; Cristina Cañero
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
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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
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Notes DAG; 600.140; 600.121; 601.269 Approved no
Call Number Admin @ si @ BRL2019 Serial 3456
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