Éditeur(s) : HAL CCSD
Résumé : National audience
Atelier "Fouille de Données Complexes" (EGC'2009)

hal-00466057
https://hal.archives-ouvertes.fr/hal-00466057

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : 17 pages, 11 figures.
International audience
The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.
ISSN: 1433-7541

hal-00329459
https://hal.archives-ouvertes.fr/hal-00329459
DOI : 10.1007/s10044-006-0038-6

Éditeur(s) : HAL CCSD
Résumé : Many works deal with the subsequence matching problem using automata structures. It is to decide, given two sequences $s$ and $t$, whether $s$ is a subsequence of $t$. Automata like the Directed Acyclic Subsequence Graph (DASG) or the Subsequence Automaton (SA) accept all subsequences of a set of texts. We focus on this last structure and provide some useful results upon dynamically updates of the SA. Indeed, sequences are indexed as soon as they are processed, allowing to dynamically add or to remove sequences from the set of indexed texts. Moreover, the highlight of these properties also makes it possible to update this automaton whenever a sequence of the set is modified.
https://hal.inria.fr/inria-00257567

inria-00257567
https://hal.inria.fr/inria-00257567
https://hal.inria.fr/inria-00257567/document
https://hal.inria.fr/inria-00257567/file/iSA.pdf

Éditeur(s) : HAL CCSD
Résumé : résumé long
National audience
17èmes rencontres de la Société Francophone de Classification (SFC'2010)

hal-00466076
https://hal.archives-ouvertes.fr/hal-00466076

Éditeur(s) : HAL CCSD
Résumé : International audience
18th International Conference on Software Engineering and Data Engineering (SEDE'09)

hal-00406165
https://hal.archives-ouvertes.fr/hal-00406165

Éditeur(s) : HAL CCSD Presses Universitaires de Louvain (distribution I6DOC/CIACO)
Résumé : In French. 10 pages, 5 figures, LaTeX 2e using EPSF and custom package taln2006.sty (designed by Pierre Zweigenbaum, ATALA). Proceedings of the 13th annual French-speaking conference on Natural Language Processing: `Traitement Automatique des Langues Naturelles' (TALN 2006), Louvain (Leuven), Belgium, 10-13 April 2003
National audience
We propose a theoretical framework within which information on the vocabulary of a given corpus can be inferred on the basis of statistical information gathered on that corpus. Inferences can be made on the categories of the words in the vocabulary, and on their syntactical properties within particular languages. Based on the same statistical data, it is possible to build matrices of syntagmatic similarity (bigram transition matrices) or paradigmatic similarity (probability for any pair of words to share common contexts). When clustered with respect to their syntagmatic similarity, words tend to group into sublanguage vocabularies, and when clustered with respect to their paradigmatic similarity, into syntactic or semantic classes. Experiments have explored the first of these two possibilities. Their results are interpreted in the frame of a Markov chain modelling of the corpus' generative processe(s): we show that the results of a spectral analysis of the transition matrix can be interpreted as probability distributions of words within clusters. This method yields a soft clustering of the vocabulary into sublanguages which contribute to the generation of heterogeneous corpora. As an application, we show how multilingual texts can be visually segmented into linguistically homogeneous segments. Our method is specifically useful in the case of related languages which happened to be mixed in corpora.
Verbum ex machina : Actes de la 13ème conférence annuelle sur le Traitement Automatique des Langues Naturelles
Louvain (Leuven), Belgium

hal-00327607
https://hal.archives-ouvertes.fr/hal-00327607
ARXIV : 0810.1212

Éditeur(s) : HAL CCSD Presses Universitaires de France
Résumé : ISBN 2-13-056651-9
Les jeunes enfants sont confrontés dès leur plus jeune âge à un environnement sémiotique où l'image et l'icône sont très présents, par le biais de leurs jouets, de leurs livres d'images, des dessins animés, et d'écrits nombreux ... Grâce à cette iconicité très stéréotypée, ils acquièrent rapidement une culture du signe iconique, apportée par l'adulte sans que celui-ci ait nécessairement conscience du contenu ainsi transmis. Par ailleurs, l'environnement scriptural de l'adulte fait lui-même une part très large à l'icône en général et au pictogramme en particulier. On sait que le pictogramme est un signe qui, malgré son caractère iconique et son apparence simple, voire simpliste, est souvent difficile à interpréter correc­tement par les adultes et que les erreurs en ce domaine sont plus fréquentes qu'on ne le croit. Le recours aux savoirs du « lecteur », aux stéréotypes scriptovisuels qu'il connaît, à son expérience, est nécessaire pour l'interprétation mais en même temps source d'erreurs. En effet, la compréhension de ces signes, loin de relever d'un réalisme naïf permettant de voir la « chose » à travers son image, requiert une compétence sémiotique et le recours à des interprétants externes, qui sont à la fois du domaine du contexte (entour du signe), et de celui de l'intertexte polysémiotique constitué par une culture intériorisé. Or le rôle de ces interprétants externes est tel que le recours à d'autres interprétants que ceux que l'émetteur du signe avait en vue peut conduire à des interprétations nettement divergentes à la lecture. Dès lors, nous nous demandons comment ces signes sont perçus par les enfants et plus particulièrement par les enfants pré-lecteurs, comment ceux-ci parviennent, ou non, à les sémiotiser, à les décrypter, à les interpréter. Nous avons donc proposé à des enfants fréquentant l'école (maternelle ou élémentaire) une série de pictogrammes. Il s'agit, en leur demandant simplement ce qu'ils comprennent, d'interroger leurs connaissances en matière de signe iconique et la manière dont ils arrivent à les réinvestir pour cons­truire du sens. Par ce biais, nous nous interrogeons également sur la manière dont ces enfants perçoivent ces signes qui ne leur sont pas spécifiquement destinés (voire pas du tout dans le cas de la signalisation routière, des pictogrammes « de gare », ou des modes d'emploi ...) mais qu'ils perçoivent cependant. Nous tentons enfin par là d'explorer la lisibilité de notre environnement scriptural « à hau­teur d'enfant ».
Les âges de la vie : Sémiotique de la culture et du temps

hal-00330427
https://hal.archives-ouvertes.fr/hal-00330427

Éditeur(s) : HAL CCSD
Résumé : International audience
In this note we study the convergence of a descent-proximal method for finding critical points of a DC function. From a practical point of view, we propose an algorithmic pattern obtained by coupling the latter with cutting plane approximations.
Journal of Applied Functional Analysis

hal-00815499
https://hal.univ-antilles.fr/hal-00815499

Éditeur(s) : HAL CCSD Yokohama
Résumé : International audience
We introduce a convergent method for approximating a common element of the set of fixed points of a nonexpansive mapping and the set of solutions of a monotone equilibrium problem. Using the main convergence theorem we obtain results which improve, develop and unify several results in fixed point problems, variational inequalities and equilibrium problems.
Journal of Nonlinear and Convex Analysis

hal-00779989
https://hal.univ-antilles.fr/hal-00779989

Éditeur(s) : HAL CCSD
Résumé : 6 pages
In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed both in time and in the network architecture. Since a current feature of SNNs is a low average activity, efficient implementations of SNNs are usually based on an Event-Driven Simulation (EDS). On the other hand, simulations of large scale neural networks can take advantage of distributing the neurons on a set of processors (either workstation cluster or parallel computer). This article presents DAMNED, a large scale SNN simulation framework able to gather the benefits of EDS and parallel computing. Two levels of parallelism are combined: Distributed mapping of the neural topology, at the network level, and local multithreaded allocation of resources for simultaneous processing of events, at the neuron level. Based on the causality of events, a distributed solution is proposed for solving the complex problem of scheduling without synchronization barrier.
https://hal.archives-ouvertes.fr/hal-00015137

hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137v2/document
https://hal.archives-ouvertes.fr/hal-00015137/file/hal_damned.pdf
ARXIV : cs.NE/0512018

Éditeur(s) : HAL CCSD Society for Industrial and Applied Mathematics
Résumé : International audience
We present iterative methods for finding the critical points and/or the minima of extended real valued functions of the form $phi = psi+ g-h$, where $psi$ is a differentiable function and g and h are convex, proper, and lower semicontinuous. The underlying idea relies upon the discretization of a first order dissipative dynamical system which allows us to preserve the local feature and to obtain some convergence results. The main theorems not only recover known convergence results in this field but also provide a theoretical basis for the development of new iterative methods.
ISSN: 1052-6234

hal-00779987
https://hal.univ-antilles.fr/hal-00779987
DOI : 10.1137/060655183

Éditeur(s) : HAL CCSD
Résumé : International audience
Abstract In this paper we prove the convergence of the approximate proximal method for DC functions proposed by Sun et al [6]. Our analysis also permits to treat the exact method. We then propose an interesting result in the case where the second component of the DC function is differentiable and provide some computational experiences which proved the efficiency of our method.
Journal of Computational Mathematics,

hal-00780885
https://hal.univ-antilles.fr/hal-00780885

Éditeur(s) : HAL CCSD IOS Press (Amsterdam)
Résumé : 6 pages, 7 embedded figures, LaTeX 2e using the ecai2006.cls document class and the algorithm2e.sty style file (+ standard packages like epsfig, amsmath, amssymb, amsfonts...). Extends the short version contained in the ECAI 2006 proceedings.
International audience
Without prior knowledge, distinguishing different languages may be a hard task, especially when their borders are permeable. We develop an extension of spectral clustering -- a powerful unsupervised classification toolbox -- that is shown to resolve accurately the task of soft language distinction. At the heart of our approach, we replace the usual hard membership assignment of spectral clustering by a soft, probabilistic assignment, which also presents the advantage to bypass a well-known complexity bottleneck of the method. Furthermore, our approach relies on a novel, convenient construction of a Markov chain out of a corpus. Extensive experiments with a readily available system clearly display the potential of the method, which brings a visually appealing soft distinction of languages that may define altogether a whole corpus.
ECAI 2006: 17th European Conference on Artificial Intelligence
Riva del Garda, Italy

hal-00327782
https://hal.archives-ouvertes.fr/hal-00327782
ARXIV : 0810.1261

Éditeur(s) : HAL CCSD IEEE Computer Society
Résumé : 5 pages, 2 figures, composed with Microsoft Word. Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003). Edinburgh, Écosse, 3-6 août 2003. Également disponible à l'URL : http://www.cse.salford.ac.uk/prima/ICDAR2003/Papers/0100_563_likforman_l.pdf
International audience
In the frame of a Unified Messaging System, a crucial task of the system is to provide the user with key information on every message received, like keywords reflecting the object of the message, or the name of the sender. However, in the case of facsimiles, this information is not as easy to detect as in the case of e-mails, since no standard headers are defined. The aim of the present work is to identify and extract a specific information (the name of the sender) from a fax cover page. For this purpose, methods based on image document analysis (OCR recognition, physical blocks selection), and text analysis methods (optimised dictionary lookup, local grammar rules), are implemented to work in parallel. The fusion of their results brings a more accurate guess than any of the methods would achieve separately.
Proceedings of the Seventh International Conference on Document Analysis and Recognition (ICDAR 2003)
Edinburgh, United Kingdom

hal-00328998
https://hal.archives-ouvertes.fr/hal-00328998
DOI : 10.1109/ICDAR.2003.1227724

Éditeur(s) : HAL CCSD Yokohama
Résumé : International audience
We make use of the viscosity technique to develop a convergent method for approximating a common element of the set of fixed points of a demicontractive operator and the set of solutions of a monotone equilibrium problem. The proposed algorithm is obtained by coupling a modified hybrid steepest descent method with the extragradient algorithm. Under mild conditions, the strong convergence of the sequences generated by the algorithm is obtained. Using this result we obtain two corollaries which improve or develop several corresponding results in this field.
Journal of Nonlinear and Convex Analysis

hal-00779988
https://hal.univ-antilles.fr/hal-00779988

Éditeur(s) : HAL CCSD
Observation des Côtes et des Océans : Senseurs et Systèmes, OCOSS 2010
Brest, France

inria-00564722
https://hal.inria.fr/inria-00564722

Éditeur(s) : HAL CCSD SpringerOpen
Résumé : International audience
We introduce methods which seem to be a new and promising tool in hierarchical fixed-point problems. The goal of this note is to analyze the convergence properties of these new types of approximating methods for fixed-point problems. The limit attained by these curves is the solution of the general variational inequality,, where denotes the normal cone to the set of fixed point of the original nonexpansive mapping and a suitable nonexpansive mapping criterion. The link with other approximation schemes in this field is also made.
ISSN: 1687-1820

hal-00780237
https://hal.univ-antilles.fr/hal-00780237
https://hal.univ-antilles.fr/hal-00780237/document
https://hal.univ-antilles.fr/hal-00780237/file/1687-1812-2006-95453.pdf
DOI : 10.1155/FPTA/2006/95453

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : International audience
Algorithms issued from the NonLinear Galerkin method have been used in many situations and with different discretizations for the resolution of evolutionary nonlinear equations. The main idea of these methods is to use a splitting of the solution in order to model the equation. According to the splitting of the solution, a splitting of the equation is obtained. The modeling principle is to freeze terms which have a small time variation. In this work we use wavelet discretizations of the 2-D Burgers equations and compare the results with the hierarchical finite elements method. The numerical tests indicate that wavelets give better results than finite elements
ISSN: 0885-7474

hal-00383423
https://hal.archives-ouvertes.fr/hal-00383423
DOI : 10.1007/s10915-004-4806-4

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
ISSN: 0377-0427

hal-00530820
https://hal.archives-ouvertes.fr/hal-00530820
DOI : 10.1016/j.cam.2008.08.014

Éditeur(s) : HAL CCSD
Résumé : This paper presents the experimental results obtained for an automatic detection of ships in High Resolution optical satellite images. Our images are panchromatic SPOT 5 images, whose resolution is 5m per pixel. Our detection method is part of an industrial project of maritime surveillance. It is based on the Bayesian decision theory and does not need any preprocessing.The detection is composed of three stages. The first one is a pre-detection of targets that gives us candidates. The second one is a precise segmentation of each candidate. The third one is a classification of candidates into three classes : real small targets, real big targets and false alarms. The two first stages are based on the bayesian theory, using a very simple image model that leads to very fast algorithms. For now, the classification is based on multivariate decision tree. Finally, the overall results of the method are given for a set of images, as close as possible to the operational conditions and show the performances of the proposed method (detection of almost all the ships, false alarms due to crests of waves and an acceptable computing time).
Journée Nationale de Photogrammétrie et Télédétection

hal-00601854
https://hal.archives-ouvertes.fr/hal-00601854