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Author (up) Adria Molina; Lluis Gomez; Oriol Ramos Terrades; Josep Llados edit   pdf
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  Title A Generic Image Retrieval Method for Date Estimation of Historical Document Collections Type Conference Article
  Year 2022 Publication Document Analysis Systems.15th IAPR International Workshop, (DAS2022) Abbreviated Journal  
  Volume 13237 Issue Pages 583–597  
  Keywords Date estimation; Document retrieval; Image retrieval; Ranking loss; Smooth-nDCG  
  Abstract Date estimation of historical document images is a challenging problem, with several contributions in the literature that lack of the ability to generalize from one dataset to others. This paper presents a robust date estimation system based in a retrieval approach that generalizes well in front of heterogeneous collections. We use a ranking loss function named smooth-nDCG to train a Convolutional Neural Network that learns an ordination of documents for each problem. One of the main usages of the presented approach is as a tool for historical contextual retrieval. It means that scholars could perform comparative analysis of historical images from big datasets in terms of the period where they were produced. We provide experimental evaluation on different types of documents from real datasets of manuscript and newspaper images.  
  Address La Rochelle, France; May 22–25, 2022  
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  Area Expedition Conference DAS  
  Notes DAG; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ MGR2022 Serial 3694  
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