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Author Marçal Rusiñol; Lluis Gomez edit   pdf
openurl 
  Title Avances en clasificación de imágenes en los últimos diez años. Perspectivas y limitaciones en el ámbito de archivos fotográficos históricos Type Journal
  Year 2018 Publication Revista anual de la Asociación de Archiveros de Castilla y León Abbreviated Journal  
  Volume 21 Issue Pages (up) 161-174  
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  Notes DAG; 600.121; 600.129 Approved no  
  Call Number Admin @ si @ RuG2018 Serial 3239  
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Author Arka Ujjal Dey; Suman Ghosh; Ernest Valveny; Gaurav Harit edit   pdf
url  doi
openurl 
  Title Beyond Visual Semantics: Exploring the Role of Scene Text in Image Understanding Type Journal Article
  Year 2021 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 149 Issue Pages (up) 164-171  
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  Abstract Images with visual and scene text content are ubiquitous in everyday life. However, current image interpretation systems are mostly limited to using only the visual features, neglecting to leverage the scene text content. In this paper, we propose to jointly use scene text and visual channels for robust semantic interpretation of images. We do not only extract and encode visual and scene text cues, but also model their interplay to generate a contextual joint embedding with richer semantics. The contextual embedding thus generated is applied to retrieval and classification tasks on multimedia images, with scene text content, to demonstrate its effectiveness. In the retrieval framework, we augment our learned text-visual semantic representation with scene text cues, to mitigate vocabulary misses that may have occurred during the semantic embedding. To deal with irrelevant or erroneous recognition of scene text, we also apply query-based attention to our text channel. We show how the multi-channel approach, involving visual semantics and scene text, improves upon state of the art.  
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  Notes DAG; 600.121 Approved no  
  Call Number Admin @ si @ DGV2021 Serial 3364  
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Author Thanh Ha Do; Oriol Ramos Terrades; Salvatore Tabbone edit  url
openurl 
  Title DSD: document sparse-based denoising algorithm Type Journal Article
  Year 2019 Publication Pattern Analysis and Applications Abbreviated Journal PAA  
  Volume 22 Issue 1 Pages (up) 177–186  
  Keywords Document denoising; Sparse representations; Sparse dictionary learning; Document degradation models  
  Abstract In this paper, we present a sparse-based denoising algorithm for scanned documents. This method can be applied to any kind of scanned documents with satisfactory results. Unlike other approaches, the proposed approach encodes noise documents through sparse representation and visual dictionary learning techniques without any prior noise model. Moreover, we propose a precision parameter estimator. Experiments on several datasets demonstrate the robustness of the proposed approach compared to the state-of-the-art methods on document denoising.  
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  Notes DAG; 600.097; 600.140; 600.121 Approved no  
  Call Number Admin @ si @ DRT2019 Serial 3254  
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Author Mathieu Nicolas Delalandre; Ernest Valveny; Tony Pridmore; Dimosthenis Karatzas edit  doi
openurl 
  Title Generation of Synthetic Documents for Performance Evaluation of Symbol Recognition & Spotting Systems Type Journal Article
  Year 2010 Publication International Journal on Document Analysis and Recognition Abbreviated Journal IJDAR  
  Volume 13 Issue 3 Pages (up) 187-207  
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  Abstract This paper deals with the topic of performance evaluation of symbol recognition & spotting systems. We propose here a new approach to the generation of synthetic graphics documents containing non-isolated symbols in a real context. This approach is based on the definition of a set of constraints that permit us to place the symbols on a pre-defined background according to the properties of a particular domain (architecture, electronics, engineering, etc.). In this way, we can obtain a large amount of images resembling real documents by simply defining the set of constraints and providing a few pre-defined backgrounds. As documents are synthetically generated, the groundtruth (the location and the label of every symbol) becomes automatically available. We have applied this approach to the generation of a large database of architectural drawings and electronic diagrams, which shows the flexibility of the system. Performance evaluation experiments of a symbol localization system show that our approach permits to generate documents with different features that are reflected in variation of localization results.  
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  Publisher Springer-Verlag Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 1433-2833 ISBN Medium  
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  Notes DAG Approved no  
  Call Number DAG @ dag @ DVP2010 Serial 1289  
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Author Marçal Rusiñol; Agnes Borras; Josep Llados edit  doi
openurl 
  Title Relational Indexing of Vectorial Primitives for Symbol Spotting in Line-Drawing Images Type Journal Article
  Year 2010 Publication Pattern Recognition Letters Abbreviated Journal PRL  
  Volume 31 Issue 3 Pages (up) 188–201  
  Keywords Document image analysis and recognition, Graphics recognition, Symbol spotting ,Vectorial representations, Line-drawings  
  Abstract This paper presents a symbol spotting approach for indexing by content a database of line-drawing images. As line-drawings are digital-born documents designed by vectorial softwares, instead of using a pixel-based approach, we present a spotting method based on vector primitives. Graphical symbols are represented by a set of vectorial primitives which are described by an off-the-shelf shape descriptor. A relational indexing strategy aims to retrieve symbol locations into the target documents by using a combined numerical-relational description of 2D structures. The zones which are likely to contain the queried symbol are validated by a Hough-like voting scheme. In addition, a performance evaluation framework for symbol spotting in graphical documents is proposed. The presented methodology has been evaluated with a benchmarking set of architectural documents achieving good performance results.  
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  Publisher Elsevier Place of Publication Editor  
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  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RBL2010 Serial 1177  
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