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Author |
F. de la Torre; Jordi Vitria; Petia Radeva; J. Melenchon |
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Title  |
EigenFiltering for flexible Eigentracking. |
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Miscellaneous |
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2000 |
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15 th International Conference on Pattern Recognition, 3:1118–1121. |
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Barcelona. |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ TVR2000 |
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179 |
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Author |
Jordi Vitria; Petia Radeva; X. Binefa |
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Title |
EigenHistograms: using low dimensional models of color distribution for real time object recognition |
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1999 |
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Ljubliana, Slovenia, Springer-Verlag |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ VRB1999a |
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29 |
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Author |
Laura Igual; Santiago Segui; Jordi Vitria; Fernando Azpiroz; Petia Radeva |
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Title |
Eigenmotion-Based Detection of Intestinal Contractions |
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Conference Article |
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2007 |
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Computer Analysis of Images and Patterns, 12th International Conference |
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4673 |
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293–300 |
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Vienna (Austria) |
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978-3-540-74271-5 |
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CAIP |
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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ ISV2007a |
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895 |
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Author |
Ricardo Toledo; X. Orriols; Petia Radeva; X. Binefa; Jordi Vitria; Cristina Cañero; Juan J. Villanueva |
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Title |
Eigensnakes for vessel segmentation in angiography. |
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Miscellaneous |
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2000 |
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15 th International Conference on Pattern Recognition, 4:340–343. |
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Barcelona. |
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OR;MILAB;ADAS;MV |
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BCNPCL @ bcnpcl @ TOR2000 |
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235 |
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Author |
Eduard Vazquez; Maria Vanrell |
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Title |
Eines per al desenvolupament de competencies de enginyeria en un assignatura de Intel·ligencia Artificial |
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Miscellaneous |
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2008 |
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V Jornades d’Innovacio Docent (UAB) |
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Bellaterra (Spain) |
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CIC |
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CAT @ cat @ VaV2008 |
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1011 |
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Author |
J.L.Bruguera; R.Casado; M.Martinez; I.Corral; Enric Marti; L.A.Branda |
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Title |
El apoyo institucional como elemento favorecedor de la coordinación docente: experiencias en diferentes universidades |
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2009 |
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Revista Red-U |
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IAM |
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IAM @ iam @ BCM2009 |
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1490 |
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Author |
I. Payan |
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Title |
El uso del recalaje en la construccion de imagenes de superresolucion |
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2001 |
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CVC Technical Report #50 |
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CVC (UAB) |
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Admin @ si @ Pay2001 |
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201 |
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Author |
Jaume Amores; Petia Radeva |
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Title |
Elastic Matching and Retrieval of IVUS Images Using Contextual Information |
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Miscellaneous |
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2003 |
Publication |
6th Catalan Conference on Artificial Intelligence (CCIA 2003), 137–148 |
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Palma de Mallorca |
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ADAS;MILAB |
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ADAS @ adas @ AmR2003a |
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364 |
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Author |
Joan Serrat; Enric Marti |
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Title |
Elastic matching using interpolation splines |
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1991 |
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IV Spanish Symposium of Pattern Recognition and image Analysis |
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ADAS;IAM; |
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IAM @ iam @ SMV1991 |
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1651 |
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Author |
Juan Ignacio Toledo; Alicia Fornes; Jordi Cucurull; Josep Llados |
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Title |
Election Tally Sheets Processing System |
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Conference Article |
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2016 |
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12th IAPR Workshop on Document Analysis Systems |
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364-368 |
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In paper based elections, manual tallies at polling station level produce myriads of documents. These documents share a common form-like structure and a reduced vocabulary worldwide. On the other hand, each tally sheet is filled by a different writer and on different countries, different scripts are used. We present a complete document analysis system for electoral tally sheet processing combining state of the art techniques with a new handwriting recognition subprocess based on unsupervised feature discovery with Variational Autoencoders and sequence classification with BLSTM neural networks. The whole system is designed to be script independent and allows a fast and reliable results consolidation process with reduced operational cost. |
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Santorini; Greece; April 2016 |
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DAS |
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DAG; 602.006; 600.061; 601.225; 600.077; 600.097 |
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TFC2016 |
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2752 |
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Author |
Francisco Cruz; Oriol Ramos Terrades |
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Title |
EM-Based Layout Analysis Method for Structured Documents |
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Conference Article |
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2014 |
Publication |
22nd International Conference on Pattern Recognition |
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315-320 |
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In this paper we present a method to perform layout analysis in structured documents. We proposed an EM-based algorithm to fit a set of Gaussian mixtures to the different regions according to the logical distribution along the page. After the convergence, we estimate the final shape of the regions according
to the parameters computed for each component of the mixture. We evaluated our method in the task of record detection in a collection of historical structured documents and performed a comparison with other previous works in this task. |
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1051-4651 |
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ICPR |
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DAG; 602.006; 600.061; 600.077 |
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Admin @ si @ CrR2014 |
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2530 |
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Author |
Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez |
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Title |
Embedded real-time stereo estimation via Semi-Global Matching on the GPU |
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Conference Article |
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2016 |
Publication |
16th International Conference on Computational Science |
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80 |
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143-153 |
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Autonomous Driving; Stereo; CUDA; 3d reconstruction |
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Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy-efficient GPU devices. Our design runs on a Tegra X1 at 41 frames per second for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. |
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San Diego; CA; USA; June 2016 |
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ADAS; 600.085; 600.082; 600.076 |
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ADAS @ adas @ HCE2016a |
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2740 |
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Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure |
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Embedded Real-time Stixel Computation |
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2017 |
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GPU Technology Conference |
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GPU; CUDA; Stixels; Autonomous Driving |
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Silicon Valley; USA; May 2017 |
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GTC |
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ADAS; 600.118 |
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ADAS @ adas @ HEV2017a |
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2879 |
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Author |
Hongxing Gao; Marçal Rusiñol; Dimosthenis Karatzas; Josep Llados |
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Title |
Embedding Document Structure to Bag-of-Words through Pair-wise Stable Key-regions |
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Conference Article |
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2014 |
Publication |
22nd International Conference on Pattern Recognition |
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2903 - 2908 |
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Since the document structure carries valuable discriminative information, plenty of efforts have been made for extracting and understanding document structure among which layout analysis approaches are the most commonly used. In this paper, Distance Transform based MSER (DTMSER) is employed to efficiently extract the document structure as a dendrogram of key-regions which roughly correspond to structural elements such as characters, words and paragraphs. Inspired by the Bag
of Words (BoW) framework, we propose an efficient method for structural document matching by representing the document image as a histogram of key-region pairs encoding structural relationships.
Applied to the scenario of document image retrieval, experimental results demonstrate a remarkable improvement when comparing the proposed method with typical BoW and pyramidal BoW methods. |
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Stockholm; Sweden; August 2014 |
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DAG; 600.056; 600.061; 600.077 |
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Admin @ si @ GRK2014b |
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2497 |
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Author |
Bogdan Raducanu; Fadi Dornaika |
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Embedding new observations via sparse-coding for non-linear manifold learning |
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Journal Article |
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2014 |
Publication |
Pattern Recognition |
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PR |
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47 |
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1 |
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480-492 |
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Non-linear dimensionality reduction techniques are affected by two critical aspects: (i) the design of the adjacency graphs, and (ii) the embedding of new test data-the out-of-sample problem. For the first aspect, the proposed solutions, in general, were heuristically driven. For the second aspect, the difficulty resides in finding an accurate mapping that transfers unseen data samples into an existing manifold. Past works addressing these two aspects were heavily parametric in the sense that the optimal performance is only achieved for a suitable parameter choice that should be known in advance. In this paper, we demonstrate that the sparse representation theory not only serves for automatic graph construction as shown in recent works, but also represents an accurate alternative for out-of-sample embedding. Considering for a case study the Laplacian Eigenmaps, we applied our method to the face recognition problem. To evaluate the effectiveness of the proposed out-of-sample embedding, experiments are conducted using the K-nearest neighbor (KNN) and Kernel Support Vector Machines (KSVM) classifiers on six public face datasets. The experimental results show that the proposed model is able to achieve high categorization effectiveness as well as high consistency with non-linear embeddings/manifolds obtained in batch modes. |
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OR;MV |
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Admin @ si @ RaD2013b |
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2316 |
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