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Author |
V. Poulain d'Andecy; Emmanuel Hartmann; Marçal Rusiñol |
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Title |
Field Extraction by hybrid incremental and a-priori structural templates |
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Conference Article |
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2018 |
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13th IAPR International Workshop on Document Analysis Systems |
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251 - 256 |
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Layout Analysis; information extraction; incremental learning |
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In this paper, we present an incremental framework for extracting information fields from administrative documents. First, we demonstrate some limits of the existing state-of-the-art methods such as the delay of the system efficiency. This is a concern in industrial context when we have only few samples of each document class. Based on this analysis, we propose a hybrid system combining incremental learning by means of itf-df statistics and a-priori generic
models. We report in the experimental section our results obtained with a dataset of real invoices. |
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Viena; Austria; April 2018 |
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DAG; 600.084; 600.129; 600.121 |
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Admin @ si @ PHR2018 |
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3106 |
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Author |
Oriol Rodriguez-Leor; E. Fernandez-Nofrerias; J. Mauri; R. Villuendas; C. Garcia; V. Valle; Cristina Cañero; Petia Radeva |
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An empiric model for three-dimensional reconstruction of coronary vessels from X-ray angiography |
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2003 |
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European Heart Journal (IF: 5.997), ESC Congress 2003 |
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Vienna |
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MILAB |
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BCNPCL @ bcnpcl @ RMF2003b |
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409 |
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Author |
Oriol Rodriguez-Leor; J. Mauri; E. Fernandez-Nofrerias; J. Lopez; M. Gomez; V. Valle; David Rotger; Petia Radeva |
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Title |
Coronary arteries three-dimensional quantification using intravascular ultrasound and angiography |
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2003 |
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European Heart Journal (IF: 5.997), ESC Congress 2003 |
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Vienna |
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MILAB |
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BCNPCL @ bcnpcl @ RMF2003d |
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411 |
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Oriol Rodriguez-Leor; E. Fernandez-Nofrerias; J. Mauri; C. Garcia; R. Villuendas; V. Valle; Oriol Pujol; Petia Radeva |
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Title |
Intravascular ultrasound segmentation using local binary patterns |
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2003 |
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European Heart Journal (IF: 5.997), ESC Congress 2003 |
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Vienna (Austria) |
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MILAB;HuPBA |
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BCNPCL @ bcnpcl @ RFM2003a |
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407 |
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Oriol Rodriguez-Leor; E. Fernandez-Nofrerias; J. Mauri; C. Garcia; R. Villuendas; V. Valle; Misael Rosales; Petia Radeva |
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Title |
Empirical simulation model of intravascular ultrasound |
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2003 |
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European Heart Journal (IF: 5.997), ESC Congress 2003 |
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Vienna (Austria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ RFM2003b |
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408 |
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Author |
Antonio Lopez; Cristina Cañero; Joan Serrat; J. Saludes; Felipe Lumbreras; T. Graf |
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Title |
Detection of lane markings based on ridgeness and RANSAC |
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Miscellaneous |
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2005 |
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Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 733–738 |
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lane markings |
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Vienna (Austria) |
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ADAS |
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ADAS @ adas @ LCS2005 |
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588 |
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Author |
Daniel Ponsa; Antonio Lopez; Felipe Lumbreras; Joan Serrat; T. Graf |
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Title |
3D Vehicle Sensor based on Monocular Vision |
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Miscellaneous |
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2005 |
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Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 1096–1101, ISBN:0–7803–9216–7 |
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Vienna (Austria) |
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ADAS |
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ADAS @ adas @ PLL2005 |
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614 |
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Author |
Daniel Ponsa; Antonio Lopez; Joan Serrat; Felipe Lumbreras; T. Graf |
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Title |
Multiple Vehicle 3D Tracking Using an Unscented Kalman Filter |
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Miscellaneous |
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2005 |
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Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems, 1108–1113, ISBN:0–7803–9216–7 |
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vehicle detection |
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Vienna (Austria) |
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ADAS |
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ADAS @ adas @ PLS2005 |
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615 |
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Author |
Joan Mas; B. Lamiroy; Gemma Sanchez; Josep Llados |
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Title |
Automatic Learning of Symbol Descriptions Avoiding Topological Ambiguities |
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Miscellaneous |
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2006 |
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3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 27–34 |
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Vienna (Austria) |
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DAG @ dag @ MLS2006b |
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710 |
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Jose Antonio Rodriguez; Gemma Sanchez; Josep Llados |
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Title |
Automatic Interpretation of Proofreading Sketches |
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2006 |
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3rd Eurographics Workshop on Sketch Based Interfaces and Modeling (SBIM´06), 35–42 |
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Vienna (Austria) |
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DAG @ dag @ RSL2006a |
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716 |
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David Rotger; Petia Radeva; E Fernandez-Nofrerias; J. Mauri |
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Title |
Blood Detection in IVUS Images for 3D Volume of Lumen Changes Measurement Due to Different Drugs Administration |
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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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285–292 |
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Vienna (Austria) |
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978-3-540-74271-5 |
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CAIP |
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MILAB |
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BCNPCL @ bcnpcl @ RRF2007b |
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832 |
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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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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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OR;MILAB;MV |
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BCNPCL @ bcnpcl @ ISV2007a |
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895 |
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David Masip; Agata Lapedriza; Jordi Vitria |
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Measuring External Face Appearance for Face Classification. |
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2007 |
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Face Recognition, Ed. Kresimir Delac and Mislav Grgic, pp. 287–307, ISBN 978–3–902613–03–5, I–Tech Education and Publishing |
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OR;MV |
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BCNPCL @ bcnpcl @ MLV2007b |
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940 |
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Florin Popescu; Stephane Ayache; Sergio Escalera; Xavier Baro; Cecile Capponi; Patrick Panciatici; Isabelle Guyon |
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From geospatial observations of ocean currents to causal predictors of spatio-economic activity using computer vision and machine learning |
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2016 |
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European Geosciences Union General Assembly |
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18 |
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The big data transformation currently revolutionizing science and industry forges novel possibilities in multimodal analysis scarcely imaginable only a decade ago. One of the important economic and industrial problems that stand to benefit from the recent expansion of data availability and computational prowess is the prediction of electricity demand and renewable energy generation. Both are correlates of human activity: spatiotemporal energy consumption patterns in society are a factor of both demand (weather dependent) and supply, which determine cost – a relation expected to strengthen along with increasing renewable energy dependence. One of the main drivers of European weather patterns is the activity of the Atlantic Ocean and in particular its dominant Northern Hemisphere current: the Gulf Stream. We choose this particular current as a test case in part due to larger amount of relevant data and scientific literature available for refinement of analysis techniques.
This data richness is due not only to its economic importance but also to its size being clearly visible in radar and infrared satellite imagery, which makes it easier to detect using Computer Vision (CV). The power of CV techniques makes basic analysis thus developed scalable to other smaller and less known, but still influential, currents, which are not just curves on a map, but complex, evolving, moving branching trees in 3D projected onto a 2D image.
We investigate means of extracting, from several image modalities (including recently available Copernicus radar and earlier Infrared satellites), a parameterized presentation of the state of the Gulf Stream and its environment that is useful as feature space representation in a machine learning context, in this case with the EC’s H2020-sponsored ‘See.4C’ project, in the context of which data scientists may find novel predictors of spatiotemporal energy flow. Although automated extractors of Gulf Stream position exist, they differ in methodology and result. We shall attempt to extract more complex feature representation including branching points, eddies and parameterized changes in transport and velocity. Other related predictive features will be similarly developed, such as inference of deep water flux long the current path and wider spatial scale features such as Hough transform, surface turbulence indicators and temperature gradient indexes along with multi-time scale analysis of ocean height and temperature dynamics. The geospatial imaging and ML community may therefore benefit from a baseline of open-source techniques useful and expandable to other related prediction and/or scientific analysis tasks. |
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Vienna; Austria; April 2016 |
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EGU |
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HuPBA;MV; |
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Admin @ si @ PAE2016 |
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2772 |
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Author |
Manuel Carbonell; Mauricio Villegas; Alicia Fornes; Josep Llados |
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Title |
Joint Recognition of Handwritten Text and Named Entities with a Neural End-to-end Model |
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Conference Article |
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2018 |
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13th IAPR International Workshop on Document Analysis Systems |
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399-404 |
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Named entity recognition; Handwritten Text Recognition; neural networks |
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When extracting information from handwritten documents, text transcription and named entity recognition are usually faced as separate subsequent tasks. This has the disadvantage that errors in the first module affect heavily the
performance of the second module. In this work we propose to do both tasks jointly, using a single neural network with a common architecture used for plain text recognition. Experimentally, the work has been tested on a collection of historical marriage records. Results of experiments are presented to show the effect on the performance for different
configurations: different ways of encoding the information, doing or not transfer learning and processing at text line or multi-line region level. The results are comparable to state of the art reported in the ICDAR 2017 Information Extraction competition, even though the proposed technique does not use any dictionaries, language modeling or post processing. |
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Vienna; Austria; April 2018 |
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Area |
|
Expedition |
|
Conference |
DAS |
|
| |
Notes |
DAG; 600.097; 603.057; 601.311; 600.121 |
Approved |
no |
|
| |
Call Number |
Admin @ si @ CVF2018 |
Serial |
3170 |
|
| Permanent link to this record |
