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Mathieu Nicolas Delalandre, Ernest Valveny and Josep Llados. 2008. Performance Evaluation of Symbol Recognition and Spotting Systems: An Overview.
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Jordi Vitria and 6 others. 1999. Real time recognition of pharmaceutical products by subspace methods.
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Gemma Sanchez, Josep Llados and K. Tombre. 2000. A mean string algorithm to compute the average among a set of 2D shapes.
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Oriol Ramos Terrades. 2003. Descripcio i classificacio de simbols tecnics usant la transformada de crestetes.
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Joan Mas. 2005. Syntactic approaches to recognize bi-dimensional shapes in graphics recognition. Application to sketching interfaces.
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Jaume Rodriguez, S. Yacoub, Gemma Sanchez and Josep Llados. 2006. Performance Evaluation, Comparison and Combination of Commercial Handwriting Recognition Engines.
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Marçal Rusiñol. 2006. A Model of Vectorial Signatures in Terms of Expressive Sub-Shapes: Symbol Indexation in Technical Documents.
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Jaime Lopez-Krahe, Josep Llados and Enric Marti. 2000. Architectural Floor Plan Analysis. University of Edinburgh.
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Josep Llados, Horst Bunke and Enric Marti. 1996. Using cyclic string matching to find rotational and reflectional symmetric shapes. In R.C. Bolles, H.B.H.N., ed. Dagstuhl Seminar on Modelling and Planning for Sensor–based Intelligent Robot Systems. Saarbrucken (Germany)., World Scientific.
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Alicia Fornes, Josep Llados, Joan Mas, Joana Maria Pujadas-Mora and Anna Cabre. 2014. A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts. Digital Access to Textual Cultural Heritage Conference.103–108.
Abstract: In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts.
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