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Author Ernest Valveny; Antonio Lopez edit   pdf
openurl 
  Title Numeral Recognition for Quality Control of Surgical Sachets Type Miscellaneous
  Year 2003 Publication Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR´03), 379–383 Abbreviated Journal  
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  Notes (down) DAG;ADAS Approved no  
  Call Number ADAS @ adas @ VaL2003 Serial 423  
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Author Marçal Rusiñol; David Aldavert; Ricardo Toledo; Josep Llados edit  url
doi  openurl
  Title Browsing Heterogeneous Document Collections by a Segmentation-Free Word Spotting Method Type Conference Article
  Year 2011 Publication 11th International Conference on Document Analysis and Recognition Abbreviated Journal  
  Volume Issue Pages 63-67  
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  Abstract In this paper, we present a segmentation-free word spotting method that is able to deal with heterogeneous document image collections. We propose a patch-based framework where patches are represented by a bag-of-visual-words model powered by SIFT descriptors. A later refinement of the feature vectors is performed by applying the latent semantic indexing technique. The proposed method performs well on both handwritten and typewritten historical document images. We have also tested our method on documents written in non-Latin scripts.  
  Address Beijing, China  
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  ISSN ISBN Medium  
  Area Expedition Conference ICDAR  
  Notes (down) DAG;ADAS Approved no  
  Call Number Admin @ si @ RAT2011 Serial 1788  
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Author Adria Rico; Alicia Fornes edit   pdf
openurl 
  Title Camera-based Optical Music Recognition using a Convolutional Neural Network Type Conference Article
  Year 2017 Publication 12th IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages 27-28  
  Keywords optical music recognition; document analysis; convolutional neural network; deep learning  
  Abstract Optical Music Recognition (OMR) consists in recognizing images of music scores. Contrary to expectation, the current OMR systems usually fail when recognizing images of scores captured by digital cameras and smartphones. In this work, we propose a camera-based OMR system based on Convolutional Neural Networks, showing promising preliminary results  
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  Area Expedition Conference GREC  
  Notes (down) DAG;600.097; 600.121 Approved no  
  Call Number Admin @ si @ RiF2017 Serial 3059  
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Author Marçal Rusiñol; David Aldavert; Dimosthenis Karatzas; Ricardo Toledo; Josep Llados edit  doi
isbn  openurl
  Title Interactive Trademark Image Retrieval by Fusing Semantic and Visual Content. Advances in Information Retrieval Type Conference Article
  Year 2011 Publication 33rd European Conference on Information Retrieval Abbreviated Journal  
  Volume 6611 Issue Pages 314-325  
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  Abstract In this paper we propose an efficient queried-by-example retrieval system which is able to retrieve trademark images by similarity from patent and trademark offices' digital libraries. Logo images are described by both their semantic content, by means of the Vienna codes, and their visual contents, by using shape and color as visual cues. The trademark descriptors are then indexed by a locality-sensitive hashing data structure aiming to perform approximate k-NN search in high dimensional spaces in sub-linear time. The resulting ranked lists are combined by using the Condorcet method and a relevance feedback step helps to iteratively revise the query and refine the obtained results. The experiments demonstrate the effectiveness and efficiency of this system on a realistic and large dataset.  
  Address Dublin, Ireland  
  Corporate Author Thesis  
  Publisher Springer Place of Publication Berlin Editor P. Clough; C. Foley; C. Gurrin; G.J.F. Jones; W. Kraaij; H. Lee; V. Murdoch  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-20160-8 Medium  
  Area Expedition Conference ECIR  
  Notes (down) DAG; RV;ADAS Approved no  
  Call Number Admin @ si @ RAK2011 Serial 1737  
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Author Ali Furkan Biten; Ruben Tito; Lluis Gomez; Ernest Valveny; Dimosthenis Karatzas edit   pdf
url  openurl
  Title OCR-IDL: OCR Annotations for Industry Document Library Dataset Type Conference Article
  Year 2022 Publication ECCV Workshop on Text in Everything Abbreviated Journal  
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  Abstract Pretraining has proven successful in Document Intelligence tasks where deluge of documents are used to pretrain the models only later to be finetuned on downstream tasks. One of the problems of the pretraining approaches is the inconsistent usage of pretraining data with different OCR engines leading to incomparable results between models. In other words, it is not obvious whether the performance gain is coming from diverse usage of amount of data and distinct OCR engines or from the proposed models. To remedy the problem, we make public the OCR annotations for IDL documents using commercial OCR engine given their superior performance over open source OCR models. The contributed dataset (OCR-IDL) has an estimated monetary value over 20K US$. It is our hope that OCR-IDL can be a starting point for future works on Document Intelligence. All of our data and its collection process with the annotations can be found in this https URL.  
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  Area Expedition Conference ECCV  
  Notes (down) DAG; no proj Approved no  
  Call Number Admin @ si @ BTG2022 Serial 3817  
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Author Carlos David Martinez Hinarejos; Josep Llados; Alicia Fornes; Francisco Casacuberta; Lluis de Las Heras; Joan Mas; Moises Pastor; Oriol Ramos Terrades; Joan Andreu Sanchez; Enrique Vidal; Fernando Vilariño edit   pdf
openurl 
  Title Context, multimodality, and user collaboration in handwritten text processing: the CoMUN-HaT project Type Conference Article
  Year 2016 Publication 3rd IberSPEECH Abbreviated Journal  
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  Abstract Processing of handwritten documents is a task that is of wide interest for many
purposes, such as those related to preserve cultural heritage. Handwritten text recognition techniques have been successfully applied during the last decade to obtain transcriptions of handwritten documents, and keyword spotting techniques have been applied for searching specific terms in image collections of handwritten documents. However, results on transcription and indexing are far from perfect. In this framework, the use of new data sources arises as a new paradigm that will allow for a better transcription and indexing of handwritten documents. Three main different data sources could be considered: context of the document (style, writer, historical time, topics,. . . ), multimodal data (representations of the document in a different modality, such as the speech signal of the dictation of the text), and user feedback (corrections, amendments,. . . ). The CoMUN-HaT project aims at the integration of these different data sources into the transcription and indexing task for handwritten documents: the use of context derived from the analysis of the documents, how multimodality can aid the recognition process to obtain more accurate transcriptions (including transcription in a modern version of the language), and integration into a userin-the-loop assisted text transcription framework. This will be reflected in the construction of a transcription and indexing platform that can be used by both professional and nonprofessional users, contributing to crowd-sourcing activities to preserve cultural heritage and to obtain an accessible version of the involved corpus.
 
  Address Lisboa; Portugal; November 2016  
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  Area Expedition Conference IberSPEECH  
  Notes (down) DAG; MV; 600.097;SIAI Approved no  
  Call Number Admin @ si @MLF2016 Serial 2813  
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Author Fernando Vilariño; Dimosthenis Karatzas; Alberto Valcarce edit  openurl
  Title The Library Living Lab Barcelona: A participative approach to technology as an enabling factor for innovation in cultural spaces Type Journal
  Year 2018 Publication Technology Innovation Management Review Abbreviated Journal  
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  Notes (down) DAG; MV; 600.097; 600.121; 600.129;SIAI Approved no  
  Call Number Admin @ si @ VKV2018a Serial 3153  
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Author Fernando Vilariño; Dimosthenis Karatzas; Alberto Valcarce edit  openurl
  Title Libraries as New Innovation Hubs: The Library Living Lab Type Conference Article
  Year 2018 Publication 30th ISPIM Innovation Conference Abbreviated Journal  
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  Abstract Libraries are in deep transformation both in EU and around the world, and they are thriving within a great window of opportunity for innovation. In this paper, we show how the Library Living Lab in Barcelona participated of this changing scenario and contributed to create the Bibliolab program, where more than 200 public libraries give voice to their users in a global user-centric innovation initiative, using technology as enabling factor. The Library Living Lab is a real 4-helix implementation where Universities, Research Centers, Public Administration, Companies and the Neighbors are joint together to explore how technology transforms the cultural experience of people. This case is an example of scalability and provides reference tools for policy making, sustainability, user engage methodologies and governance. We provide specific examples of new prototypes and services that help to understand how to redefine the role of the Library as a real hub for social innovation.  
  Address Stockholm; May 2018  
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  Area Expedition Conference ISPIM  
  Notes (down) DAG; MV; 600.097; 600.121; 600.129;SIAI Approved no  
  Call Number Admin @ si @ VKV2018b Serial 3154  
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Author Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez edit  openurl
  Title Symbol Recognition by Multi-class Blurred Shape Models Type Conference Article
  Year 2007 Publication Seventh IAPR International Workshop on Graphics Recognition Abbreviated Journal  
  Volume Issue Pages 11–13  
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  Address Curitiba (Brazil)  
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  Area Expedition Conference GREC  
  Notes (down) DAG; MILAB; HUPBA Approved no  
  Call Number BCNPCL @ bcnpcl @ FEL2007b Serial 910  
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Author Dena Bazazian; Raul Gomez; Anguelos Nicolaou; Lluis Gomez; Dimosthenis Karatzas; Andrew Bagdanov edit   pdf
openurl 
  Title Improving Text Proposals for Scene Images with Fully Convolutional Networks Type Conference Article
  Year 2016 Publication 23rd International Conference on Pattern Recognition Workshops Abbreviated Journal  
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  Abstract Text Proposals have emerged as a class-dependent version of object proposals – efficient approaches to reduce the search space of possible text object locations in an image. Combined with strong word classifiers, text proposals currently yield top state of the art results in end-to-end scene text
recognition. In this paper we propose an improvement over the original Text Proposals algorithm of [1], combining it with Fully Convolutional Networks to improve the ranking of proposals. Results on the ICDAR RRC and the COCO-text datasets show superior performance over current state-of-the-art.
 
  Address Cancun; Mexico; December 2016  
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  Area Expedition Conference ICPRW  
  Notes (down) DAG; LAMP; 600.084 Approved no  
  Call Number Admin @ si @ BGN2016 Serial 2823  
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