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Carolina Malagelada; F.De Lorio; Fernando Azpiroz; Santiago Segui; Petia Radeva; Anna Accarino; J.Santos; Juan R. Malagelada |
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Intestinal Dysmotility in Patients with Functional Intestinal Disorders Demonstrated by Computer Vision Analysis of Capsule Endoscopy Images |
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Conference Article |
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2010 |
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18th United European Gastroenterology Week |
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56 |
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3 |
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A19-20 |
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Barcelona |
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UEGW |
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MILAB |
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Admin @ si @ MLA2010 |
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1779 |
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Author |
N. Serrano; L. Tarazon; D. Perez; Oriol Ramos Terrades; S. Juan |
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Title |
The GIDOC Prototype |
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Conference Article |
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Year |
2010 |
Publication |
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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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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Monica Piñol |
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Adaptative Vocabulary Tree for Image Classification using Reinforcement Learning |
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Report |
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2010 |
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CVC Technical Report |
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162 |
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Bellaterra (Barcelona) |
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Computer Vision Center |
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Master's thesis |
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Admin @ si @ Piñ2010 |
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1936 |
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Jean-Marc Ogier; Wenyin Liu; Josep Llados (eds) |
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Title |
Graphics Recognition: Achievements, Challenges, and Evolution |
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Book Whole |
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2010 |
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8th International Workshop GREC 2009. |
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6020 |
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La Rochelle |
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Springer Link |
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Jean-Marc Ogier; Wenyin Liu; Josep Llados |
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Lecture Notes in Computer Science |
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978-3-642-13727-3 |
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GREC |
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Admin @ si @ OLL2010 |
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1976 |
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Author |
Joan Arnedo-Moreno; Agata Lapedriza |
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Title |
Visualizing key authenticity: turning your face into your public key |
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2010 |
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6th China International Conference on Information Security and Cryptology |
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605-618 |
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Biometric information has become a technology complementary to cryptography, allowing to conveniently manage cryptographic data. Two important needs are ful lled: rst of all, making such data always readily available, and additionally, making its legitimate owner easily identi able. In this work we propose a signature system which integrates face recognition biometrics with and identity-based signature scheme, so the user's face e ectively becomes his public key and system ID. Thus, other users may verify messages using photos of the claimed sender, providing a reasonable trade-o between system security and usability, as well as a much more straightforward public key authenticity and distribution process. |
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LNCS |
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Inscrypt |
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OR;MV |
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Admin @ si @ ArL2010c |
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2149 |
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