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Author Pau Riba; Anjan Dutta; Josep Llados; Alicia Fornes; Sounak Dey edit   pdf
openurl 
  Title Improving Information Retrieval in Multiwriter Scenario by Exploiting the Similarity Graph of Document Terms Type Conference Article
  Year 2017 Publication 14th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages (down) 475-480  
  Keywords document terms; information retrieval; affinity graph; graph of document terms; multiwriter; graph diffusion  
  Abstract Information Retrieval (IR) is the activity of obtaining information resources relevant to a questioned information. It usually retrieves a set of objects ranked according to the relevancy to the needed fact. In document analysis, information retrieval receives a lot of attention in terms of symbol and word spotting. However, through decades the community mostly focused either on printed or on single writer scenario, where the
state-of-the-art results have achieved reasonable performance on the available datasets. Nevertheless, the existing algorithms do not perform accordingly on multiwriter scenario. A graph representing relations between a set of objects is a structure where each node delineates an individual element and the similarity between them is represented as a weight on the connecting edge. In this paper, we explore different analytics of graphs constructed from words or graphical symbols, such as diffusion, shortest path, etc. to improve the performance of information retrieval methods in multiwriter scenario
 
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  Notes DAG; 600.097; 601.302; 600.121 Approved no  
  Call Number Admin @ si @ RDL2017a Serial 3053  
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Author Josep Llados; Felipe Lumbreras; V. Chapaprieta; J. Queralt edit  openurl
  Title ICAR: Identity Card Automatic Reader. Type Miscellaneous
  Year 2001 Publication Sixth International Conference on Document Analysis and Recognition Abbreviated Journal ICDAR 2001  
  Volume Issue Pages (down) 470–474  
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  Address USA  
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  Notes ADAS;DAG Approved no  
  Call Number ADAS @ adas @ LLC2001 Serial 112  
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Author Lluis Gomez; Dimosthenis Karatzas edit   pdf
doi  openurl
  Title Multi-script Text Extraction from Natural Scenes Type Conference Article
  Year 2013 Publication 12th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages (down) 467-471  
  Keywords  
  Abstract Scene text extraction methodologies are usually based in classification of individual regions or patches, using a priori knowledge for a given script or language. Human perception of text, on the other hand, is based on perceptual organisation through which text emerges as a perceptually significant group of atomic objects. Therefore humans are able to detect text even in languages and scripts never seen before. In this paper, we argue that the text extraction problem could be posed as the detection of meaningful groups of regions. We present a method built around a perceptual organisation framework that exploits collaboration of proximity and similarity laws to create text-group hypotheses. Experiments demonstrate that our algorithm is competitive with state of the art approaches on a standard dataset covering text in variable orientations and two languages.  
  Address Washington; USA; August 2013  
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  Series Volume Series Issue Edition  
  ISSN 1520-5363 ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes DAG; 600.056; 601.158; 601.197 Approved no  
  Call Number Admin @ si @ GoK2013 Serial 2310  
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Author Lei Kang; Juan Ignacio Toledo; Pau Riba; Mauricio Villegas; Alicia Fornes; Marçal Rusiñol edit   pdf
url  openurl
  Title Convolve, Attend and Spell: An Attention-based Sequence-to-Sequence Model for Handwritten Word Recognition Type Conference Article
  Year 2018 Publication 40th German Conference on Pattern Recognition Abbreviated Journal  
  Volume Issue Pages (down) 459-472  
  Keywords  
  Abstract This paper proposes Convolve, Attend and Spell, an attention based sequence-to-sequence model for handwritten word recognition. The proposed architecture has three main parts: an encoder, consisting of a CNN and a bi-directional GRU, an attention mechanism devoted to focus on the pertinent features and a decoder formed by a one-directional GRU, able to spell the corresponding word, character by character. Compared with the recent state-of-the-art, our model achieves competitive results on the IAM dataset without needing any pre-processing step, predefined lexicon nor language model. Code and additional results are available in https://github.com/omni-us/research-seq2seq-HTR.  
  Address Stuttgart; Germany; October 2018  
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  Area Expedition Conference GCPR  
  Notes DAG; 600.097; 603.057; 302.065; 601.302; 600.084; 600.121; 600.129 Approved no  
  Call Number Admin @ si @ KTR2018 Serial 3167  
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Author Josep Llados; Gemma Sanchez edit  openurl
  Title Graph Matching vs. Graph Parsing in Graphics Recognition: A Combined Approach Type Journal
  Year 2004 Publication International Journal of Pattern Recognition and Artificial Intelligence Abbreviated Journal IJPRAI  
  Volume 18 Issue 3 Pages (down) 455–473  
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  Notes DAG; IF: 0.588 Approved no  
  Call Number DAG @ dag @ LlS2004 Serial 445  
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Author Ernest Valveny; Enric Marti edit   pdf
doi  openurl
  Title Learning of structural descriptions of graphic symbols using deformable template matching Type Conference Article
  Year 2001 Publication Proc. Sixth Int Document Analysis and Recognition Conf Abbreviated Journal  
  Volume Issue Pages (down) 455-459  
  Keywords  
  Abstract Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching.  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VMA2001 Serial 1654  
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Author Jon Almazan; David Fernandez; Alicia Fornes; Josep Llados; Ernest Valveny edit   pdf
doi  isbn
openurl 
  Title A Coarse-to-Fine Approach for Handwritten Word Spotting in Large Scale Historical Documents Collection Type Conference Article
  Year 2012 Publication 13th International Conference on Frontiers in Handwriting Recognition Abbreviated Journal  
  Volume Issue Pages (down) 453-458  
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  Abstract In this paper we propose an approach for word spotting in handwritten document images. We state the problem from a focused retrieval perspective, i.e. locating instances of a query word in a large scale dataset of digitized manuscripts. We combine two approaches, namely one based on word segmentation and another one segmentation-free. The first approach uses a hashing strategy to coarsely prune word images that are unlikely to be instances of the query word. This process is fast but has a low precision due to the errors introduced in the segmentation step. The regions containing candidate words are sent to the second process based on a state of the art technique from the visual object detection field. This discriminative model represents the appearance of the query word and computes a similarity score. In this way we propose a coarse-to-fine approach achieving a compromise between efficiency and accuracy. The validation of the model is shown using a collection of old handwritten manuscripts. We appreciate a substantial improvement in terms of precision regarding the previous proposed method with a low computational cost increase.  
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  ISSN ISBN 978-1-4673-2262-1 Medium  
  Area Expedition Conference ICFHR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ AFF2012 Serial 1983  
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Author Joan Mas; Gemma Sanchez; Josep Llados; B. Lamiroy edit  openurl
  Title An Incremental On-line Parsing Algorithm for Recognizing Sketching Diagrams Type Conference Article
  Year 2007 Publication 9th IEEE International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume 1 Issue Pages (down) 452–456  
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  Address Curitiba (Brazil)  
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  Area Expedition Conference ICDAR  
  Notes DAG Approved no  
  Call Number DAG @ dag @ MSL2007a Serial 847  
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Author Alicia Fornes; Beata Megyesi; Joan Mas edit   pdf
openurl 
  Title Transcription of Encoded Manuscripts with Image Processing Techniques Type Conference Article
  Year 2017 Publication Digital Humanities Conference Abbreviated Journal  
  Volume Issue Pages (down) 441-443  
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  Area Expedition Conference DH  
  Notes DAG; 600.097; 600.121 Approved no  
  Call Number Admin @ si @ FMM2017 Serial 3061  
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Author Francesc Tous; Agnes Borras; Robert Benavente; Ramon Baldrich; Maria Vanrell; Josep Llados edit  openurl
  Title Textual Descriptions for Browsing People by Visual Apperance. Type Book Chapter
  Year 2002 Publication Lecture Notes in Artificial Intelligence Abbreviated Journal  
  Volume 2504 Issue Pages (down) 419-429  
  Keywords  
  Abstract This paper presents a first approach to build colour and structural descriptors for information retrieval on a people database. Queries are formulated in terms of their appearance that allows to seek people wearing specific clothes of a given colour name or texture. Descriptors are automatically computed by following three essential steps. A colour naming labelling from pixel properties. A region seg- mentation step based on colour properties of pixels combined with edge information. And a high level step that models the region arrangements in order to build clothes structure. Results are tested on large set of images from real scenes taken at the entrance desk of a building  
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  Publisher Springer Verlag Place of Publication Editor  
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  Notes DAG;CIC Approved no  
  Call Number CAT @ cat @ TBB2002b Serial 319  
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