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Author |
Nuria Cirera; Alicia Fornes; Volkmar Frinken; Josep Llados |
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Title |
Hybrid grammar language model for handwritten historical documents recognition |
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Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
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Volume |
7887 |
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Pages |
117-124 |
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In this paper we present a hybrid language model for the recognition of handwritten historical documents with a structured syntactical layout. Using a hidden Markov model-based recognition framework, a word-based grammar with a closed dictionary is enhanced by a character sequence recognition method. This allows to recognize out-of-dictionary words in controlled parts of the recognition, while keeping a closed vocabulary restriction for other parts. While the current status is work in progress, we can report an improvement in terms of character error rate. |
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Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-38627-5 |
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IbPRIA |
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DAG; 602.006; 600.045; 600.061 |
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Call Number |
Admin @ si @ CFF2013 |
Serial |
2292 |
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Author |
D.Sanchez; J.C.Ortega; Miguel Angel Bautista |
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Title |
Human Body Segmentation with Multi-limb Error-Correcting Output Codes Detection and Graph Cuts Optimization |
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Conference Article |
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Year |
2013 |
Publication |
6th Iberian Conference on Pattern Recognition and Image Analysis |
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7887 |
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50-58 |
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Keywords |
Human Body Segmentation; Error-Correcting Output Codes; Cascade of Classifiers; Graph Cuts |
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Abstract |
Human body segmentation is a hard task because of the high variability in appearance produced by changes in the point of view, lighting conditions, and number of articulations of the human body. In this paper, we propose a two-stage approach for the segmentation of the human body. In a first step, a set of human limbs are described, normalized to be rotation invariant, and trained using cascade of classifiers to be split in a tree structure way. Once the tree structure is trained, it is included in a ternary Error-Correcting Output Codes (ECOC) framework. This first classification step is applied in a windowing way on a new test image, defining a body-like probability map, which is used as an initialization of a GMM color modelling and binary Graph Cuts optimization procedure. The proposed methodology is tested in a novel limb-labelled data set. Results show performance improvements of the novel approach in comparison to classical cascade of classifiers and human detector-based Graph Cuts segmentation approaches. |
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Madeira; Portugal; June 2013 |
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Springer Berlin Heidelberg |
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0302-9743 |
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978-3-642-38627-5 |
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IbPRIA |
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HUPBA |
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Call Number |
SOB2013 |
Serial |
2250 |
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Author |
Joan Serrat; J. Argemi; Juan J. Villanueva |
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Title |
Automatization of TW2 method using a knowledge-based image analysis system. |
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Conference Article |
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Year |
1991 |
Publication |
VIth International Congress of Auxology. |
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Madrid |
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ADAS |
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ADAS @ adas @ SAV1991 |
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259 |
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Author |
Francisco Jose Perales; Yuhua Luo; Juan J. Villanueva |
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Title |
Un metodo Automatico de Rotoscopia Sin Marcas para el Estudio del Movimiento Humano Basado en un modelo Biomecanico. |
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Conference Article |
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Year |
1991 |
Publication |
Primer Congreso Español de Informatica Grafica |
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53-65 |
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Madrid |
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ISE @ ise @ PLV1991 |
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266 |
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Author |
M. Gomez; J. Mauri; E. Fernandez-Nofrerias; Oriol Rodriguez-Leor; Carme Julia; Oriol Pujol; Petia Radeva |
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Title |
Diferenciacion de las estructuras del vaso coronario mediante el procesamiento de imagenes y el analisis de las diferentes texturas a partir de la ecografia intracoronaria |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiologia |
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Madrid |
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MILAB;HuPBA |
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no |
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Call Number |
BCNPCL @ bcnpcl @ GMF2002f |
Serial |
433 |
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Author |
Cristina Cañero; Petia Radeva; M. Gomez; J. Mauri; E. Fernandez-Nofrerias; Oriol Rodriguez-Leor; C. Julia |
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Title |
Modelo experimental para la reconstruccion tridimensional de las arterias coronarias a partir de imagenes de coronariografia |
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2002 |
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Madrid |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ GMF2002e |
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434 |
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Author |
Laura Igual; Joan Carles Soliva; Antonio Hernandez; Sergio Escalera; Oscar Vilarroya; Petia Radeva |
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Title |
Supervised Brain Segmentation and Classification in Diagnostic of Attention-Deficit/Hyperactivity Disorder |
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Conference Article |
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2012 |
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High Performance Computing and Simulation, International Conference on |
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182-187 |
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This paper presents an automatic method for external and internal segmentation of the caudate nucleus in Magnetic Resonance Images (MRI) based on statistical and structural machine learning approaches. This method is applied in Attention-Deficit/Hyperactivity Disorder (ADHD) diagnosis. The external segmentation method adapts the Graph Cut energy-minimization model to make it suitable for segmenting small, low-contrast structures, such as the caudate nucleus. In particular, new energy function data and boundary potentials are defined and a supervised energy term based on contextual brain structures is added. Furthermore, the internal segmentation method learns a classifier based on shape features of the Region of Interest (ROI) in MRI slices. The results show accurate external and internal caudate segmentation in a real data set and similar performance of ADHD diagnostic test to manual annotation. |
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Madrid |
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IEEE Xplore |
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978-1-4673-2359-8 |
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HPCS |
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MILAB;HuPBA |
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no |
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Call Number |
Admin @ si @ ISH2012a |
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2038 |
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Author |
Robert Benavente; Maria Vanrell |
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Title |
Parametrizacion del Espacio de Categorias de Color |
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Miscellaneous |
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2007 |
Publication |
Proceedings del VIII Congreso Nacional del Color |
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77–78 |
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Madrid (Spain) |
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CNC’07 |
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CAT;CIC |
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CAT @ cat @ BeV2007 |
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905 |
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Author |
Jorge Bernal; F. Javier Sanchez; Fernando Vilariño |
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Title |
Reduction of Pattern Search Area in Colonoscopy Images by Merging Non-Informative Regions |
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Conference Article |
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2010 |
Publication |
28th Congreso Anual de la Sociedad Española de Ingeniería Biomédica |
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One of the first usual steps in pattern recognition schemas is image segmentation, in order to reduce the dimensionality of the problem and manage smaller quantity of data. In our case as we are pursuing real-time colon cancer polyp detection, this step is crucial. In this paper we present a non-informative region estimation algorithm that will let us discard some parts of the image where we will not expect to find colon cancer polyps. The performance of our approach will be measured in terms of both non-informative areas elimination and polyps’ areas preserving. The results obtained show the importance of having correct non- informative region estimation in order to fasten the whole recognition process. |
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Madrid (Spain) |
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800 |
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CASEIB |
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MV;SIAI |
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no |
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Call Number |
Admin @ si @ BSV2010 |
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1469 |
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Author |
Gloria Fernandez Esparrach; Jorge Bernal; Cristina Rodriguez de Miguel; Debora Gil; Fernando Vilariño; Henry Cordova; Cristina Sanchez Montes; Isis Ara |
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Title |
Utilidad de la visión por computador para la localización de pólipos pequeños y planos |
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Conference Article |
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2016 |
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XIX Reunión Nacional de la Asociación Española de Gastroenterología, Gastroenterology Hepatology |
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39 |
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2 |
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94 |
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Madrid (Spain) |
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AEGASTRO |
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MV; IAM; 600.097;SIAI |
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Admin @ si @FBR2016 |
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2779 |
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Author |
M. Gomez; J. Mauri; E. Fernandez-Nofrerias; Oriol Rodriguez-Leor; Carme Julia; Misael Rosales; Petia Radeva |
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Modelo fisico para la simulacion de ultrasonido Intravascular. |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiologia. |
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Madrid, Espanya |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ GMF2002b |
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308 |
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Author |
M. Gomez; J. Mauri; E. Fernandez-Nofrerias; Oriol Rodriguez-Leor; Carme Julia; Petia Radeva; David Rotger; V. Valle |
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Nuevos Avances para la correlacion de imagenes angiograficas y de ecograia intracoronaria. |
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Miscellaneous |
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2002 |
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Congreso de las Enfermedades Cardiovasculares, XXXVIII Congreso de la Sociedad Española de Cardiologia. |
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Madrid, Espanya |
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MILAB |
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BCNPCL @ bcnpcl @ GMF2002c |
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309 |
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Author |
Eduardo Aguilar; Petia Radeva |
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Title |
Food Recognition by Integrating Local and Flat Classifiers |
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Conference Article |
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2019 |
Publication |
9th Iberian Conference on Pattern Recognition and Image Analysis |
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11867 |
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65-74 |
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The recognition of food image is an interesting research topic, in which its applicability in the creation of nutritional diaries stands out with the aim of improving the quality of life of people with a chronic disease (e.g. diabetes, heart disease) or prone to acquire it (e.g. people with overweight or obese). For a food recognition system to be useful in real applications, it is necessary to recognize a huge number of different foods. We argue that for very large scale classification, a traditional flat classifier is not enough to acquire an acceptable result. To address this, we propose a method that performs prediction with local classifiers, based on a class hierarchy, or with flat classifier. We decide which approach to use, depending on the analysis of both the Epistemic Uncertainty obtained for the image in the children classifiers and the prediction of the parent classifier. When our criterion is met, the final prediction is obtained with the respective local classifier; otherwise, with the flat classifier. From the results, we can see that the proposed method improves the classification performance compared to the use of a single flat classifier. |
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Madrid; July 2019 |
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IbPRIA |
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MILAB; no proj |
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Admin @ si @ AgR2019b |
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3369 |
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Author |
Gemma Rotger; Francesc Moreno-Noguer; Felipe Lumbreras; Antonio Agudo |
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Single view facial hair 3D reconstruction |
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Conference Article |
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2019 |
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9th Iberian Conference on Pattern Recognition and Image Analysis |
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11867 |
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423-436 |
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3D Vision; Shape Reconstruction; Facial Hair Modeling |
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n this work, we introduce a novel energy-based framework that addresses the challenging problem of 3D reconstruction of facial hair from a single RGB image. To this end, we identify hair pixels over the image via texture analysis and then determine individual hair fibers that are modeled by means of a parametric hair model based on 3D helixes. We propose to minimize an energy composed of several terms, in order to adapt the hair parameters that better fit the image detections. The final hairs respond to the resulting fibers after a post-processing step where we encourage further realism. The resulting approach generates realistic facial hair fibers from solely an RGB image without assuming any training data nor user interaction. We provide an experimental evaluation on real-world pictures where several facial hair styles and image conditions are observed, showing consistent results and establishing a comparison with respect to competing approaches. |
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Madrid; July 2019 |
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IbPRIA |
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ADAS; 600.086; 600.130; 600.122 |
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Admin @ si @ |
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3707 |
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Author |
Alicia Fornes; Josep Llados; Joan Mas; Joana Maria Pujadas-Mora; Anna Cabre |
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Title |
A Bimodal Crowdsourcing Platform for Demographic Historical Manuscripts |
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Conference Article |
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Year |
2014 |
Publication |
Digital Access to Textual Cultural Heritage Conference |
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Pages |
103-108 |
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Abstract |
In this paper we present a crowdsourcing web-based application for extracting information from demographic handwritten document images. The proposed application integrates two points of view: the semantic information for demographic research, and the ground-truthing for document analysis research. Concretely, the application has the contents view, where the information is recorded into forms, and the labeling view, with the word labels for evaluating document analysis techniques. The crowdsourcing architecture allows to accelerate the information extraction (many users can work simultaneously), validate the information, and easily provide feedback to the users. We finally show how the proposed application can be extended to other kind of demographic historical manuscripts. |
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Address |
Madrid; May 2014 |
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ISSN |
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ISBN |
978-1-4503-2588-2 |
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DATeCH |
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Notes |
DAG; 600.061; 602.006; 600.077 |
Approved |
no |
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Call Number |
Admin @ si @ FLM2014 |
Serial |
2516 |
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