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Joan Mas; Gemma Sanchez; Josep Llados |
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Title |
An Adjacency Grammar to Recognize Symbols and Gestures in a Digital Pen Framework |
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2005 |
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Pattern Recognition and Image Analysis (IbPRIA 2005), LNCS 3523: 115–122 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Estoril (Portugal) |
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DAG @ dag @ MSL2005a |
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558 |
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Asma Bensalah; Antonio Parziale; Giuseppe De Gregorio; Angelo Marcelli; Alicia Fornes; Josep Llados |
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Title |
I Can’t Believe It’s Not Better: In-air Movement for Alzheimer Handwriting Synthetic Generation |
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2023 |
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21st International Graphonomics Conference |
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136–148 |
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During recent years, there here has been a boom in terms of deep learning use for handwriting analysis and recognition. One main application for handwriting analysis is early detection and diagnosis in the health field. Unfortunately, most real case problems still suffer a scarcity of data, which makes difficult the use of deep learning-based models. To alleviate this problem, some works resort to synthetic data generation. Lately, more works are directed towards guided data synthetic generation, a generation that uses the domain and data knowledge to generate realistic data that can be useful to train deep learning models. In this work, we combine the domain knowledge about the Alzheimer’s disease for handwriting and use it for a more guided data generation. Concretely, we have explored the use of in-air movements for synthetic data generation. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Evora; Portugal; October 2023 |
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Admin @ si @ BPG2023 |
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3838 |
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Veronica Romero; Alicia Fornes; Enrique Vidal; Joan Andreu Sanchez |
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Title |
Information Extraction in Handwritten Marriage Licenses Books Using the MGGI Methodology |
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Conference Article |
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2017 |
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8th Iberian Conference on Pattern Recognition and Image Analysis |
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10255 |
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287-294 |
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Handwritten Text Recognition; Information extraction; Language modeling; MGGI; Categories-based language model |
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Historical records of daily activities provide intriguing insights into the life of our ancestors, useful for demographic and genealogical research. For example, marriage license books have been used for centuries by ecclesiastical and secular institutions to register marriages. These books follow a simple structure of the text in the records with a evolutionary vocabulary, mainly composed of proper names that change along the time. This distinct vocabulary makes automatic transcription and semantic information extraction difficult tasks. In previous works we studied the use of category-based language models and how a Grammatical Inference technique known as MGGI could improve the accuracy of these tasks. In this work we analyze the main causes of the semantic errors observed in previous results and apply a better implementation of the MGGI technique to solve these problems. Using the resulting language model, transcription and information extraction experiments have been carried out, and the results support our proposed approach. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Faro; Portugal; June 2017 |
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L.A. Alexandre; J.Salvador Sanchez; Joao M. F. Rodriguez |
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LNCS |
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978-3-319-58837-7 |
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IbPRIA |
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DAG; 602.006; 600.097; 600.121 |
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Admin @ si @ RFV2017 |
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2952 |
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Hana Jarraya; Oriol Ramos Terrades; Josep Llados |
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Title |
Graph Embedding through Probabilistic Graphical Model applied to Symbolic Graphs |
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Conference Article |
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2017 |
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8th Iberian Conference on Pattern Recognition and Image Analysis |
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Attributed Graph; Probabilistic Graphical Model; Graph Embedding; Structured Support Vector Machines |
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We propose a new Graph Embedding (GEM) method that takes advantages of structural pattern representation. It models an Attributed Graph (AG) as a Probabilistic Graphical Model (PGM). Then, it learns the parameters of this PGM presented by a vector. This vector is a signature of AG in a lower dimensional vectorial space. We apply Structured Support Vector Machines (SSVM) to process classification task. As first tentative, results on the GREC dataset are encouraging enough to go further on this direction. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Faro; Portugal; June 2017 |
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IbPRIA |
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DAG; 600.097; 600.121 |
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Admin @ si @ JRL2017a |
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2953 |
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Author |
Josep Llados |
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Title |
Perspectives on the Analysis of Graphical Documents |
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Miscellaneous |
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2006 |
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Colloque International Francophone sur l´Ecrit et le Document (CIFED´06), 25–31 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Fribourg (Switzerland) |
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DAG @ dag @ Lla2006a |
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706 |
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Agnes Borras; Josep Llados |
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Title |
A Multi-Scale Layout Descriptor Based on Delaunay Triangulation for Image Retrieval |
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2008 |
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3rd International Conference on Computer Vision Theory and Applications VISAPP (2) 2008 |
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2 |
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139-144 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Funchal, Madeira (Portugal) |
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DAG @ dag @ BoL2008 |
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981 |
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N. Serrano; L. Tarazon; D. Perez; Oriol Ramos Terrades; S. Juan |
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Title |
The GIDOC Prototype |
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2010 |
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10th International Workshop on Pattern Recognition in Information Systems |
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82-89 |
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Transcription of handwritten text in (old) documents is an important, time-consuming task for digital libraries. It might be carried out by first processing all document images off-line, and then manually supervising system transcriptions to edit incorrect parts. However, current techniques for automatic page layout analysis, text line detection and handwriting recognition are still far from perfect, and thus post-editing system output is not clearly better than simply ignoring it.
A more effective approach to transcribe old text documents is to follow an interactive- predictive paradigm in which both, the system is guided by the user, and the user is assisted by the system to complete the transcription task as efficiently as possible. Following this approach, a system prototype called GIDOC (Gimp-based Interactive transcription of old text DOCuments) has been developed to provide user-friendly, integrated support for interactive-predictive layout analysis, line detection and handwriting transcription.
GIDOC is designed to work with (large) collections of homogeneous documents, that is, of similar structure and writing styles. They are annotated sequentially, by (par- tially) supervising hypotheses drawn from statistical models that are constantly updated with an increasing number of available annotated documents. And this is done at different annotation levels. For instance, at the level of page layout analysis, GIDOC uses a novel text block detection method in which conventional, memoryless techniques are improved with a “history” model of text block positions. Similarly, at the level of text line image transcription, GIDOC includes a handwriting recognizer which is steadily improved with a growing number of (partially) supervised transcriptions. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Funchal, Portugal |
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978-989-8425-14-0 |
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Admin @ si @ STP2010 |
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1868 |
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Alicia Fornes; Sergio Escalera; Josep Llados; Gemma Sanchez; Petia Radeva; Oriol Pujol |
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Title |
Handwritten Symbol Recognition by a Boosted Blurred Shape Model with Error Correction |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:13–21 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Girona (Spain) |
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MILAB;DAG;HUPBA |
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BCNPCL @ bcnpcl @ FEL2007a |
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775 |
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Author |
Agnes Borras; Josep Llados |
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Title |
Similarity-Based Object Retrieval Using Appearance and Geometric Feature Combination |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4477:113–120 |
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4478 |
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33–39 |
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This work presents a content-based image retrieval system of general purpose that deals with cluttered scenes containing a given query object. The system is flexible enough to handle with a single image of an object despite its rotation, translation and scale variations. The image content is divided in parts that are described with a combination of features based on geometrical and color properties. The idea behind the feature combination is to benefit from a fuzzy similarity computation that provides robustness and tolerance to the retrieval process. The features can be independently computed and the image parts can be easily indexed by using a table structure on every feature value. Finally a process inspired in the alignment strategies is used to check the coherence of the object parts found in a scene. Our work presents a system of easy implementation that uses an open set of features and can suit a wide variety of applications. |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Girona (Spain) |
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978-3-540-72848-1 |
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DAG; |
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DAG @ dag @ BoL2007a; IAM @ iam @ BoL2007a |
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776 |
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Author |
Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Rejection strategies involving classifier combination for handwriting recognition |
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2007 |
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3rd Iberian Conference on Pattern Recognition and Image Analysis (IbPRIA 2007), J. Marti et al. (Eds.) LNCS 4478:97–104 |
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Address ![sorted by Address field, ascending order (up)](http://refbase.cvc.uab.es/img/sort_asc.gif) |
Girona (Spain) |
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DAG @ dag @ RSL2007a |
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777 |
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