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Author |
Joan Mas; B. Lamiroy; Gemma Sanchez; Josep Llados |

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Title |
Automatic Adjacency Grammar Generation from User Drawn Sketches |
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2006 |
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18th International Conference on Pattern Recognition (ICPR´06), 2: 1026–1029 |
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Hong Kong |
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DAG |
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DAG @ dag @ MLS2006a |
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709 |
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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 |
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DAG @ dag @ MLS2006b |
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710 |
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Author |
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 |
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DAG @ dag @ RSL2006a |
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716 |
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Author |
Oriol Ramos Terrades; Salvatore Tabbone; Ernest Valveny |

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Title |
Combination of shape descriptors using an adaptation of boosting |
Type  |
Miscellaneous |
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Year |
2006 |
Publication |
18th International Conference on Pattern Recognition (ICPR´06), 2: 764–767 |
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Hong Kong |
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DAG |
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DAG @ dag @ RTV2006 |
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718 |
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Author |
Miquel Ferrer; Robert Benavente; Ernest Valveny; J. Garcia; Agata Lapedriza; Gemma Sanchez |

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Title |
Aprendizaje Cooperativo Aplicado a la Docencia de las Asignaturas de Programacion en Ingenieria Informatica |
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Miscellaneous |
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Year |
2008 |
Publication |
Octava Jornada sobre Aprendizaje Cooperativo, 41–46 |
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Lleida (Spain). |
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OR;DAG;CIC;MV |
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no |
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BCNPCL @ bcnpcl @ FBV2008 |
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955 |
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Author |
Agata Lapedriza; Jaume Garcia; Ernest Valveny; Robert Benavente; Miquel Ferrer; Gemma Sanchez |

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Title |
Una experiencia de aprenentatge basada en projectes en el ambit de la informatica |
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Miscellaneous |
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2008 |
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V Jornades d’Innovacio Docent (UAB) |
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63 |
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Bellaterra (Spain) |
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OR; IAM; DAG; CIC; MV |
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no |
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BCNPCL @ bcnpcl @ LGV2008 |
Serial |
1030 |
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Author |
Robert Benavente; Ernest Valveny; Jaume Garcia; Agata Lapedriza; Miquel Ferrer; Gemma Sanchez |

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Title |
Una experiencia de adaptacion al EEES de las asignaturas de programacion en Ingenieria Informatica |
Type  |
Miscellaneous |
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2008 |
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V Congreso Iberoamericano de Docencia Universitaria, pp. 213–216 |
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Valencia |
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OR;DAG;CIC;MV |
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no |
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BCNPCL @ bcnpcl @ BVG2008 |
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1031 |
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Author |
Ernest Valveny; Robert Benavente; Agata Lapedriza; Miquel Ferrer; Jaume Garcia; Gemma Sanchez |


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Title |
Adaptation of a computer programming course to the EXHE requirements: evaluation five years later |
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Miscellaneous |
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2012 |
Publication |
European Journal of Engineering Education |
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37 |
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3 |
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243-254 |
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DAG; CIC; OR; invisible;MV |
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no |
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Admin @ si @ VBL2012 |
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2070 |
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Author |
Carles Sanchez; Oriol Ramos Terrades; Patricia Marquez; Enric Marti; Jaume Rocarias; Debora Gil |

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Title |
Evaluación automática de prácticas en Moodle para el aprendizaje autónomo en Ingenierías |
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Miscellaneous |
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2014 |
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8th International Congress on University Teaching and Innovation |
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Tarragona; juliol 2014 |
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CIDUI |
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IAM; 600.075;DAG |
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Admin @ si @ SRM2014 |
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2458 |
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Author |
Sounak Dey; Anjan Dutta; Juan Ignacio Toledo; Suman Ghosh; Josep Llados; Umapada Pal |


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Title |
SigNet: Convolutional Siamese Network for Writer Independent Offline Signature Verification |
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2018 |
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Arxiv |
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Abstract |
Offline signature verification is one of the most challenging tasks in biometrics and document forensics. Unlike other verification problems, it needs to model minute but critical details between genuine and forged signatures, because a skilled falsification might often resembles the real signature with small deformation. This verification task is even harder in writer independent scenarios which is undeniably fiscal for realistic cases. In this paper, we model an offline writer independent signature verification task with a convolutional Siamese network. Siamese networks are twin networks with shared weights, which can be trained to learn a feature space where similar observations are placed in proximity. This is achieved by exposing the network to a pair of similar and dissimilar observations and minimizing the Euclidean distance between similar pairs while simultaneously maximizing it between dissimilar pairs. Experiments conducted on cross-domain datasets emphasize the capability of our network to model forgery in different languages (scripts) and handwriting styles. Moreover, our designed Siamese network, named SigNet, exceeds the state-of-the-art results on most of the benchmark signature datasets, which paves the way for further research in this direction. |
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DAG; 600.097; 600.121 |
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Admin @ si @ DDT2018 |
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3085 |
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