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Author Partha Pratim Roy; Umapada Pal; Josep Llados edit  openurl
  Title (down) Recognition of Multi-oriented Touching Characters in Graphical Documents Type Conference Article
  Year 2008 Publication Computer Vision, Graphics & Image Processing, 2008. Sixth Indian Conference on, Abbreviated Journal  
  Volume 16 Issue Pages 297–304  
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  ISSN ISBN Medium  
  Area Expedition Conference ICVGIP ’08  
  Notes DAG Approved no  
  Call Number DAG @ dag @ RPL2008c Serial 1080  
Permanent link to this record
 

 
Author Ernest Valveny; Enric Marti edit  openurl
  Title (down) Recognition of lineal symbols in hand-written drawings using deformable template matching Type Conference Article
  Year 1999 Publication Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Análisis de Imágenes Abbreviated Journal  
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  Notes DAG;IAM; Approved no  
  Call Number IAM @ iam @ VAM1999 Serial 1658  
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Author Nuria Cirera edit  openurl
  Title (down) Recognition of Handwritten Historical Documents Type Report
  Year 2012 Publication CVC Technical Report Abbreviated Journal  
  Volume 174 Issue Pages  
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  Corporate Author Thesis Master's thesis  
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  Area Expedition Conference  
  Notes DAG Approved no  
  Call Number Admin @ si @ Cir2012 Serial 2416  
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Author Muhammad Muzzamil Luqman; Thierry Brouard; Jean-Yves Ramel; Josep Llados edit  openurl
  Title (down) Recherche de sous-graphes par encapsulation floue des cliques d'ordre 2: Application à la localisation de contenu dans les images de documents graphiques Type Conference Article
  Year 2012 Publication Colloque International Francophone sur l'Écrit et le Document Abbreviated Journal  
  Volume Issue Pages 149-162  
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  Area Expedition Conference CIFED  
  Notes DAG Approved no  
  Call Number Admin @ si @ LBR2012 Serial 2382  
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Author Antonio Lopez; Ernest Valveny; Juan J. Villanueva edit  url
openurl 
  Title (down) Real-time quality control of surgical material packaging by artificial vision Type Journal Article
  Year 2005 Publication Assembly Automation Abbreviated Journal  
  Volume 25 Issue 3 Pages  
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  Abstract IF: 0.061)  
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  Notes ADAS;DAG Approved no  
  Call Number ADAS @ adas @ LVV2005 Serial 552  
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Author Andres Mafla; Ruben Tito; Sounak Dey; Lluis Gomez; Marçal Rusiñol; Ernest Valveny; Dimosthenis Karatzas edit  url
openurl 
  Title (down) Real-time Lexicon-free Scene Text Retrieval Type Journal Article
  Year 2021 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 110 Issue Pages 107656  
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  Abstract In this work, we address the task of scene text retrieval: given a text query, the system returns all images containing the queried text. The proposed model uses a single shot CNN architecture that predicts bounding boxes and builds a compact representation of spotted words. In this way, this problem can be modeled as a nearest neighbor search of the textual representation of a query over the outputs of the CNN collected from the totality of an image database. Our experiments demonstrate that the proposed model outperforms previous state-of-the-art, while offering a significant increase in processing speed and unmatched expressiveness with samples never seen at training time. Several experiments to assess the generalization capability of the model are conducted in a multilingual dataset, as well as an application of real-time text spotting in videos.  
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  Notes DAG; 600.121; 600.129; 601.338 Approved no  
  Call Number Admin @ si @ MTD2021 Serial 3493  
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Author Jordi Vitria; Petia Radeva; X. Binefa; A. Pujol; Ernest Valveny; Robert Benavente; Craig Von Land edit  openurl
  Title (down) Real time recognition of pharmaceutical products by subspace methods Type Report
  Year 1999 Publication CVC Technical Report #35 Abbreviated Journal  
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  Address CVC (UAB)  
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  Notes OR;MILAB;DAG;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ VRB1999b Serial 54  
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Author A. Pujol; Jordi Vitria; Petia Radeva; X. Binefa; Robert Benavente; Ernest Valveny; Craig Von Land edit  openurl
  Title (down) Real time pharmaceutical product recognition using color and shape indexing. Type Conference Article
  Year 1999 Publication Proceedings of the 2nd International Workshop on European Scientific and Industrial Collaboration (WESIC´99), Promotoring Advanced Technologies in Manufacturing. Abbreviated Journal  
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  Address Wales  
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  Notes OR;MILAB;DAG;CIC;MV Approved no  
  Call Number BCNPCL @ bcnpcl @ PVR1999 Serial 24  
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Author Leonardo Galteri; Dena Bazazian; Lorenzo Seidenari; Marco Bertini; Andrew Bagdanov; Anguelos Nicolaou; Dimosthenis Karatzas; Alberto del Bimbo edit   pdf
doi  openurl
  Title (down) Reading Text in the Wild from Compressed Images Type Conference Article
  Year 2017 Publication 1st International workshop on Egocentric Perception, Interaction and Computing Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Reading text in the wild is gaining attention in the computer vision community. Images captured in the wild are almost always compressed to varying degrees, depending on application context, and this compression introduces artifacts
that distort image content into the captured images. In this paper we investigate the impact these compression artifacts have on text localization and recognition in the wild. We also propose a deep Convolutional Neural Network (CNN) that can eliminate text-specific compression artifacts and which leads to an improvement in text recognition. Experimental results on the ICDAR-Challenge4 dataset demonstrate that compression artifacts have a significant
impact on text localization and recognition and that our approach yields an improvement in both – especially at high compression rates.
 
  Address Venice; Italy; October 2017  
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  ISSN ISBN Medium  
  Area Expedition Conference ICCV - EPIC  
  Notes DAG; 600.084; 600.121 Approved no  
  Call Number Admin @ si @ GBS2017 Serial 3006  
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Author Arnau Baro edit  isbn
openurl 
  Title (down) Reading Music Systems: From Deep Optical Music Recognition to Contextual Methods Type Book Whole
  Year 2022 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
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  Abstract The transcription of sheet music into some machine-readable format can be carried out manually. However, the complexity of music notation inevitably leads to burdensome software for music score editing, which makes the whole process
very time-consuming and prone to errors. Consequently, automatic transcription
systems for musical documents represent interesting tools.
Document analysis is the subject that deals with the extraction and processing
of documents through image and pattern recognition. It is a branch of computer
vision. Taking music scores as source, the field devoted to address this task is
known as Optical Music Recognition (OMR). Typically, an OMR system takes an
image of a music score and automatically extracts its content into some symbolic
structure such as MEI or MusicXML.
In this dissertation, we have investigated different methods for recognizing a
single staff section (e.g. scores for violin, flute, etc.), much in the same way as most text recognition research focuses on recognizing words appearing in a given line image. These methods are based in two different methodologies. On the one hand, we present two methods based on Recurrent Neural Networks, in particular, the
Long Short-Term Memory Neural Network. On the other hand, a method based on Sequence to Sequence models is detailed.
Music context is needed to improve the OMR results, just like language models
and dictionaries help in handwriting recognition. For example, syntactical rules
and grammars could be easily defined to cope with the ambiguities in the rhythm.
In music theory, for example, the time signature defines the amount of beats per
bar unit. Thus, in the second part of this dissertation, different methodologies
have been investigated to improve the OMR recognition. We have explored three
different methods: (a) a graphic tree-structure representation, Dendrograms, that
joins, at each level, its primitives following a set of rules, (b) the incorporation of Language Models to model the probability of a sequence of tokens, and (c) graph neural networks to analyze the music scores to avoid meaningless relationships between music primitives.
Finally, to train all these methodologies, and given the method-specificity of
the datasets in the literature, we have created four different music datasets. Two of them are synthetic with a modern or old handwritten appearance, whereas the
other two are real handwritten scores, being one of them modern and the other
old.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher IMPRIMA Place of Publication Editor Alicia Fornes  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-124793-8-6 Medium  
  Area Expedition Conference  
  Notes DAG; Approved no  
  Call Number Admin @ si @ Bar2022 Serial 3754  
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