Дисертації з теми "Analyse supervisée de graphes"
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Faucheux, Cyrille. "Segmentation supervisée d'images texturées par régularisation de graphes." Thesis, Tours, 2013. http://www.theses.fr/2013TOUR4050/document.
Повний текст джерелаIn this thesis, we improve a recent image segmentation algorithm based on a graph regularization process. The goal of this method is to compute an indicator function that satisfies a regularity and a fidelity criteria. Its particularity is to represent images with similarity graphs. This data structure allows relations to be established between similar pixels, leading to non-local processing of the data. In order to improve this approach, combine it with another non-local one: the texture features. Two solutions are developped, both based on Haralick features. In the first one, we propose a new fidelity term which is based on the work of Chan and Vese and is able to evaluate the homogeneity of texture features. In the second method, we propose to replace the fidelity criteria by the output of a supervised classifier. Trained to recognize several textures, the classifier is able to produce a better modelization of the problem by identifying the most relevant texture features. This method is also extended to multiclass segmentation problems. Both are applied to 2D and 3D textured images
Fontaine, Michaël. "Segmentation non supervisée d'images couleur par analyse de la connexité des pixels." Lille 1, 2001. https://pepite-depot.univ-lille.fr/LIBRE/Th_Num/2001/50376-2001-305-306.pdf.
Повний текст джерелаRibeyre, Corentin. "Méthodes d’analyse supervisée pour l’interface syntaxe-sémantique : de la réécriture de graphes à l’analyse par transitions." Sorbonne Paris Cité, 2016. http://www.theses.fr/2016USPCC119.
Повний текст джерелаNowadays, the amount of textual data has become so gigantic, that it is not possible to deal with it manually. In fact, it is now necessary to use Natural Language Processing techniques to extract useful information from these data and understand their underlying meaning. In this thesis, we offer resources, models and methods to allow: (i) the automatic annotation of deep syntactic corpora to extract argument structure that links (verbal) predicates to their arguments (ii) the use of these resources with the help of efficient methods. First, we develop a graph rewriting system and a set of manually-designed rewriting rules to automatically annotate deep syntax in French. Thanks to this approach, two corpora were created: the DeepSequoia, a deep syntactic version of the Séquoia corpus and the DeepFTB, a deep syntactic version of the dependency version of the French Treebank. Next, we extend two transition-based parsers and adapt them to be able to deal with graph structures. We also develop a set of rich linguistic features extracted from various syntactic trees. We think they are useful to bring different kind of topological information to accurately predict predicat-argument structures. Used in an arc-factored second-order parsing model, this set of features gives the first state-of-the-art results on French and outperforms the one established on the DM and PAS corpora for English. Finally, we briefly explore a method to automatically induce the transformation between a tree and a graph. This completes our set of coherent resources and models to automatically analyze the syntax-semantics interface on French and English
Pujari, Manisha. "Prévision de liens dans des grands graphes de terrain (application aux réseaux bibliographiques)." Thesis, Sorbonne Paris Cité, 2015. http://www.theses.fr/2015USPCD010/document.
Повний текст джерелаIn this work, we are interested to tackle the problem of link prediction in complex networks. In particular, we explore topological dyadic approaches for link prediction. Different topological proximity measures have been studied in the scientific literature for finding the probability of appearance of new links in a complex network. Supervided learning methods have also been used to combine the predictions made or information provided by different topological measures. The create predictive models using various topological measures. The problem of supervised learning for link prediction is a difficult problem especially due to the presence of heavy class imbalance. In this thesis, we search different alternative approaches to improve the performance of different dyadic approaches for link prediction. We propose here, a new approach of link prediction based on supervised rank agregation that uses concepts from computational social choice theory. Our approach is founded on supervised techniques of aggregating sorted lists (or preference aggregation). We also explore different ways of improving supervised link prediction approaches. One approach is to extend the set of attributes describing an example (pair of nodes) by attributes calculated in a multiplex network that includes the target network. Multiplex networks have a layered structure, each layer having different kinds of links between same sets of nodes. The second way is to use community information for sampling of examples to deal with the problem of classe imabalance. Experiments conducted on real networks extracted from well known DBLP bibliographic database
Sevi, Harry. "Analyse harmonique sur graphes dirigés et applications : de l'analyse de Fourier aux ondelettes." Thesis, Lyon, 2018. http://www.theses.fr/2018LYSEN068/document.
Повний текст джерелаThe research conducted in this thesis aims to develop a harmonic analysis for functions defined on the vertices of an oriented graph. In the era of data deluge, much data is in the form of graphs and data on this graph. In order to analyze and exploit this graph data, we need to develop mathematical and numerically efficient methods. This development has led to the emergence of a new theoretical framework called signal processing on graphs, which aims to extend the fundamental concepts of conventional signal processing to graphs. Inspired by the multi-scale aspect of graphs and graph data, many multi-scale constructions have been proposed. However, they apply only to the non-directed framework. The extension of a harmonic analysis on an oriented graph, although natural, is complex. We, therefore, propose a harmonic analysis using the random walk operator as the starting point for our framework. First, we propose Fourier-type bases formed by the eigenvectors of the random walk operator. From these Fourier bases, we determine a frequency notion by analyzing the variation of its eigenvectors. The determination of a frequency analysis from the basis of the vectors of the random walk operator leads us to multi-scale constructions on oriented graphs. More specifically, we propose a wavelet frame construction as well as a decimated wavelet construction on directed graphs. We illustrate our harmonic analysis with various examples to show its efficiency and relevance
Galluccio, Laurent. "Analyse et segmentation de données non supervisées à l'aide de graphe." Nice, 2010. http://www.theses.fr/2010NICE4022.
Повний текст джерелаThis thesis presents new data segmentation and data clustering methods applied to astrophysical data. A priori information such as the number of classes or the underlying data distribution is not necessarily known. Many classification methods in astrophysics community are based on a priori knowledges or on observations already realized on data. Classifications obtained will depend on these information and will be limited by the experts knowledge. The goal of developing clustering algorithms is to get rid of these limitations, to be able to potentially detect new classes. The main approach chosen in this thesis is the use of a graph built on the data : the Minimal Spanning Tree (MST). By connecting the points by segments we build a structure which encapsulates the being relations between each pair of points. We propose a method to estimate both the number and the position of clusters by exploring the connections of the MST built. A data partition is obtained by using this information to initialize some clustering algorithms. A new class of multi-rooted MSTs is introduced. From their construction, new distance measures are derived allowing to take into account both the local and global data neighborhood. A clustering method which combines results of multiple partitionments realized on the multi-rooted trees is also exposed. The methods proposed are validated on benchmarks and applied to astrophysical datasets
Fontaine, Michaël Macaire Ludovic Postaire Jack-Gérard. "Segmentation non supervisée d'images couleur par analyse de la connexité des pixels." [S.l.] : [s.n.], 2001. http://www.univ-lille1.fr/bustl-grisemine/pdf/extheses/50376-2001-305-306.pdf.
Повний текст джерелаGaillard, Pierre. "Apprentissage statistique de la connexité d'un nuage de points par modèle génératif : application à l'analyse exploratoire et la classification semi-supervisée." Compiègne, 2008. http://www.theses.fr/2008COMP1767.
Повний текст джерелаIn this work, we propose a statistical model to learn the connectedness of a set of points. This model combine geometrical and statistical approaches by defining a mixture model based on a graph. From this generative graph, we propose and evaluate methods and algorithms to analyse the set of points and to realize semi-supervised learning
Gan, Changquan. "Une approche de classification non supervisée basée sur la notion des K plus proches voisins." Compiègne, 1994. http://www.theses.fr/1994COMP765S.
Повний текст джерелаCorneli, Marco. "Dynamic stochastic block models, clustering and segmentation in dynamic graphs." Thesis, Paris 1, 2017. http://www.theses.fr/2017PA01E012/document.
Повний текст джерелаThis thesis focuses on the statistical analysis of dynamic graphs, both defined in discrete or continuous time. We introduce a new extension of the stochastic block model (SBM) for dynamic graphs. The proposed approach, called dSBM, adopts non homogeneous Poisson processes to model the interaction times between pairs of nodes in dynamic graphs, either in discrete or continuous time. The intensity functions of the processes only depend on the node clusters, in a block modelling perspective. Moreover, all the intensity functions share some regularity properties on hidden time intervals that need to be estimated. A recent estimation algorithm for SBM, based on the greedy maximization of an exact criterion (exact ICL) is adopted for inference and model selection in dSBM. Moreover, an exact algorithm for change point detection in time series, the "pruned exact linear time" (PELT) method is extended to deal with dynamic graph data modelled via dSBM. The approach we propose can be used for change point analysis in graph data. Finally, a further extension of dSBM is developed to analyse dynamic net- works with textual edges (like social networks, for instance). In this context, the graph edges are associated with documents exchanged between the corresponding vertices. The textual content of the documents can provide additional information about the dynamic graph topological structure. The new model we propose is called "dynamic stochastic topic block model" (dSTBM).Graphs are mathematical structures very suitable to model interactions between objects or actors of interest. Several real networks such as communication networks, financial transaction networks, mobile telephone networks and social networks (Facebook, Linkedin, etc.) can be modelled via graphs. When observing a network, the time variable comes into play in two different ways: we can study the time dates at which the interactions occur and/or the interaction time spans. This thesis only focuses on the first time dimension and each interaction is assumed to be instantaneous, for simplicity. Hence, the network evolution is given by the interaction time dates only. In this framework, graphs can be used in two different ways to model networks. Discrete time […] Continuous time […]. In this thesis both these perspectives are adopted, alternatively. We consider new unsupervised methods to cluster the vertices of a graph into groups of homogeneous connection profiles. In this manuscript, the node groups are assumed to be time invariant to avoid possible identifiability issues. Moreover, the approaches that we propose aim to detect structural changes in the way the node clusters interact with each other. The building block of this thesis is the stochastic block model (SBM), a probabilistic approach initially used in social sciences. The standard SBM assumes that the nodes of a graph belong to hidden (disjoint) clusters and that the probability of observing an edge between two nodes only depends on their clusters. Since no further assumption is made on the connection probabilities, SBM is a very flexible model able to detect different network topologies (hubs, stars, communities, etc.)
Sharma, Avinash. "Représentation et enregistrement de formes visuelles 3D à l'aide de Laplacien graphe et noyau de la chaleur." Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00860533.
Повний текст джерелаDebeir, Olivier. "Segmentation supervisée d'images." Doctoral thesis, Universite Libre de Bruxelles, 2001. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/211474.
Повний текст джерелаLe, Boudic-Jamin Mathilde. "Similarités et divergences, globales et locales, entre structures protéiques." Thesis, Rennes 1, 2015. http://www.theses.fr/2015REN1S119/document.
Повний текст джерелаThis thesis focusses on local and global similarities and divergences inside protein structures. First, structures are scored, with criteria of similarity and distance in order to provide a supervised classification. This structural domain classification inside existing hierarchical databases is possible by using dominances and learning. These methods allow to assign new domains with accuracy and exactly. Second we focusses on local similarities and proposed a method of protein comparison modelisation inside graphs. Graph traversal allows to find protein similar substructures. This method is based on compatibility between elements and criterion of distances. We can use it and detect events such that circular permutations, hinges and structural motif repeats. Finally we propose a new approach of accurate protein structure analysis that focused on divergences between similar structures
Goubet, Étienne. "Contrôle non destructif par analyse supervisée d'images 3D ultrasonores." Cachan, Ecole normale supérieure, 1999. http://www.theses.fr/1999DENS0011.
Повний текст джерелаCoupechoux, Emilie. "Analyse de grands graphes aléatoires." Paris 7, 2012. http://www.theses.fr/2012PA077184.
Повний текст джерелаSeveral kinds of real-world networks can be represented by graphs. Since such networks are very large, their detailed topology is generally unknown, and we model them by large random graphs having the same local statistical properties as the observed networks. An example of such properties is the fact that real-world networks are often highly clustered : if two individuals have a friend in common, they are likely to also be each other's friends. Studying random graph models that are both appropriate and tractable from a mathematical point of view is challenging, that is why we consider several clustered random graph models. The spread of epidemics in random graphs can be used to model several kinds of phenomena in real-world networks, as the spread of diseases, or the diffusion of a new technology. The epidemic model we consider depends on the phenomenon we wish to represent :. An individual can contract a disease by a single contact with any of his friends (such contacts being independent),. But a new technology is likely to be adopted by an individual if many of his friends already have the technology in question. We essentially study these two cases. In each case, one wants to know if a small proportion of the population initially infected (or having the technology in question) can propagate the epidemic to a large part of the population
Huck, Alexis. "Analyse non-supervisée d’images hyperspectrales : démixage linéaire et détection d’anomalies." Aix-Marseille 3, 2009. http://www.theses.fr/2009AIX30036.
Повний текст джерелаThis thesis focusses on two research fields regarding unsupervised analysis of hyperspectral images (HSIs). Under the assumptions of the linear spectral mixing model, the formalism of Non-Negative Matrix Factorization is investigated for unmixing purposes. We propose judicious spectral and spatial a priori knowledge to regularize the problem. In addition, we propose an estimator for the projected gradient optimal step-size. Thus, suitably regularized NMF is shown to be a relevant approach to unmix HSIs. Then, the problem of anomaly detection is considered. We propose an algorithm for Anomalous Component Pursuit (ACP), simultaneously based on projection pursuit and on a probabilistic model and hypothesis testing. ACP detects the anomalies with a constant false alarm rate and discriminates them into spectrally homogeneous classes
Hamidouche, Mounia. "Analyse spectrale de graphes géométriques aléatoires." Thesis, Université Côte d'Azur, 2020. http://www.theses.fr/2020COAZ4019.
Повний текст джерелаWe study random geometric graphs (RGGs) to address key problems in complex networks. An RGG is constructed by uniformly distributing n nodes on a torus of dimension d and connecting two nodes if their distance does not exceed a certain threshold. Three regimes for RGGs are of particular interest. The connectivity regime in which the average vertex degree a_n grows logarithmically with n or faster. The dense regime in which a_n is linear with n. The thermodynamic regime in which a_n is a constant. We study the spectrum of RGGs normalized Laplacian (LN) and its regularized version in the three regimes. When d is fixed and n tends to infinity we prove that the limiting spectral distribution (LSD) of LN converges to Dirac distribution at 1 in the connectivity regime. In the thermodynamic regime we propose an approximation for LSD of the regularized NL and we provide an error bound on the approximation. We show that LSD of the regularized LN of an RGG is approximated by LSD of the regularized LN of a deterministic geometric graph (DGG). We study LSD of RGGs adjacency matrix in the connectivity regime. Under some conditions on a_n we show that LSD of DGGs adjacency matrix is a good approximation for LSD of RGGs for n large. We determine the spectral dimension (SD) that characterizes the return time distribution of a random walk on RGGs. We show that SD depends on the eigenvalue density (ED) of the RGG normalized Laplacian in the neighborhood of the minimum eigenvalues. Based on the analytical eigenvalues of the normalized Laplacian we show that ED in a neighborhood of the minimum value follows a power-law tail and we approximate SD of RGGs by d in the thermodynamic regime
Dimon, Catalin. "Contributions à la modélisation et la commande des réseaux de trafic routier." Phd thesis, Ecole Centrale de Lille, 2012. http://tel.archives-ouvertes.fr/tel-00801762.
Повний текст джерелаPanafieu, Elie de. "Combinatoire analytique des graphes, hypergraphes et graphes inhomogènes." Paris 7, 2014. http://www.theses.fr/2014PA077167.
Повний текст джерелаWe investigate two graph-like models: the non-uniform hypergraphs and the inhomogeneous graphs. They are close to the models defined by Darling and Norris (2004) and Sôderberg (2002). We enumerate them and derive structure information before and near the birth of the giant component. The inhomogeneous graph model proves to be a convenient framework for the modeling of several tractable constraint satisfaction problems (CSP), such as the 2-colorability problem, the satisfiability of 2-Xor formulas and of quantified 2-Xor formulas. We link the probability of satisfiability of those problems to the enumeration of inhomogeneous graphs. As an application, proofs of old and new phase transition results are derived in a unified framework. Finally, we derive a new simple proof for the asymptotic number of connected multigraphs with a number of edges proportional to the number of vertices. This result was first derived for simple graphs by Bender, Canfield and McKay (1990). The main tool of this thesis is analytic combinatorics, as defined by Flajolet and Sedgewick in their book (2009)
Dârlea, Georgiana-Lavinia. "Un système de classification supervisée à base de règles implicatives." Chambéry, 2010. http://www.theses.fr/2010CHAMS001.
Повний текст джерелаThis PhD thesis presents a series of research works done in the field of supervised data classification more precisely in the domain of semi-automatic learning of fuzzy rules-based classifiers. The prepared manuscript presents first an overview of the classification problem, and also of the main classification methods that have already been implemented and certified in order to place the proposed method in the general context of the domain. Once the context established, the actual research work is presented: the definition of a formal background for representing an elementary fuzzy rule-based classifier in a bi-dimensional space, the description of a learning algorithm for these elementary classifiers for a given data set and the conception of a multi-dimensional classification system which is able to handle multi-classes problems by combining the elementary classifiers. The implementation and testing of all these functionalities and finally the application of the resulted classifier on two real-world digital image problems are finally presented: the analysis of the quality of industrial products using 3D tomographic images and the identification of regions of interest in radar satellite images
Conan-Guez, Brieuc. "Modélisation supervisée de données fonctionnelles par perceptron multi-couches." Phd thesis, Université Paris Dauphine - Paris IX, 2002. http://tel.archives-ouvertes.fr/tel-00178892.
Повний текст джерелаLeblanc, Brice. "Analyse non supervisée de données issues de Systèmes de Transport Intelligent-Coopératif." Thesis, Reims, 2020. http://www.theses.fr/2020REIMS014.
Повний текст джерелаThis thesis takes place in the context of Vehicular Ad-hoc Networks (VANET), and more specifically the context of Cooperative-Intelligent Transport System (C-ITS). These systems are exchanging information to enhance road safety.The purpose of this thesis is to introduce data analysis tools that may provide road operators information on the usage/state of their infrastructures. Therefore, this information may help to improve road safety. We identify two cases we want to deal with: driving profile identification and road obstacle detection.For dealing with those issues, we propose to use unsupervised learning approaches: clustering methods for driving profile identification, and concept drift detection for obstacle detection. This thesis introduces three main contributions: a methodology allowing us to transform raw C-ITS data in, first, trajectory, and then, learning data-set; the use of classical clustering methods and Points Of Interests for driving profiles with experiments on mobile device data and network logs data; and the consideration of a crowd of vehicles providing network log data as data streams and considered as input of concept drift detection algorithms to recognize road obstacles
Vandewalle, Vincent. "Estimation et sélection en classification semi-supervisée." Phd thesis, Université des Sciences et Technologie de Lille - Lille I, 2009. http://tel.archives-ouvertes.fr/tel-00447141.
Повний текст джерелаGodard, Emmanuel. "Réécritures de graphes et algorithmique distribuée." Bordeaux 1, 2002. http://www.theses.fr/2002BOR12518.
Повний текст джерелаMostefaoui, Mustapha. "Analyse des propriétés temporelles des graphes d'événements valués continus." Nantes, 2001. http://www.theses.fr/2001NANT2100.
Повний текст джерелаAlbano, Alice. "Dynamique des graphes de terrain : analyse en temps intrinsèque." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066260/document.
Повний текст джерелаWe are surrounded by a multitude of interaction networks from different contexts. These networks can be modeled as graphs, called complex networks. They have a community structure, i.e. groups of nodes closely related to each other and less connected with the rest of the graph. An other phenomenon studied in complex networks in many contexts is diffusion. The spread of a disease is an example of diffusion. These phenomena are dynamic and depend on an important parameter, which is often little studied: the time scale in which they are observed. According to the chosen scale, the graph dynamics can vary significantly. In this thesis, we propose to study dynamic processes using a suitable time scale. We consider a notion of relative time which we call intrinsic time, opposed to "traditional" time, which we call extrinsic time. We first study diffusion phenomena using intrinsic time, and we compare our results with an extrinsic time scale. This allows us to highlight the fact that the same phenomenon observed at two different time scales can have a very different behavior. We then analyze the relevance of the use of intrinsic time scale for detecting dynamic communities. Comparing communities obtained according extrinsic and intrinsic scales shows that the intrinsic time scale allows a more significant detection than extrinsic time scale
Janaqi, Stefan. "Quelques éléments de la géométrie des graphes : graphes médians, produits d'arbres, génération convexe des graphes de Polymino." Université Joseph Fourier (Grenoble), 1994. http://www.theses.fr/1995GRE10093.
Повний текст джерелаMercier, Lucas. "Grands graphes et grands arbres aléatoires : analyse du comportement asymptotique." Thesis, Université de Lorraine, 2016. http://www.theses.fr/2016LORR0028/document.
Повний текст джерелаThis thesis is dedicated to the study of the asymptotic behavior of some large random graphs and trees. First is studied a random graph model introduced by Bo Söderberg in 2002. One chapter of this manuscript is devoted to the study of the asymptotic behavior of the size of the connected components near the critical window, linking it to the lengths of excursion of a Brownian motion with parabolic drift. The next chapter talks about a random graph process suggested by Itai Benjamini, defined as follows: edges are independently added at a fixe rate. Whenever a vertex reaches degree k, all adjacent edges are removed. This process is non-increasing, preventing the use of some commonly used methods. By using local limits, in the spirit of the PWIT, we were able to prove the presence (resp. absence) of a giant component at some stages of the process when k>=5 (resp. k<=3). In the case k=4, these results allows to link the presence (resp. absence) of a giant component to the supercriticality (resp. criticality or subcriticality) of an associated branching process. In the last chapter, the height of random Lyndon tree is studied, and is proven to be approximately c ln n, in which c=5.092... the solution of an optimization problem. To obtain this result, we couple the Lyndon tree with a Yule tree, then studied with the help of branching walks and large deviations
Ravelomanana, Vlady. "Graphes multicycliques étiquetés : aspects combinatoires et probabilistes." Amiens, 2000. http://www.theses.fr/2000AMIE0122.
Повний текст джерелаCutrona, Jérôme. "Analyse de forme des objets biologiques : représentation, classification et suivi temporel." Reims, 2003. http://www.theses.fr/2003REIMS018.
Повний текст джерелаN biology, the relationship between shape, a major element in computer vision, and function has been emphasized since a long time. This thesis proposes a processing line leading to unsupervised shape classification, deformation tracking and supervised classification of whole population of objects. We first propose a contribution to unsupervised segmentation based on a fuzzy classification method and two semi-automatic methods founded on fuzzy connectedness and watersheds. Next, we perform a study on several shape descriptors including primitives and anti-primitives, contour, silhouete and multi-scale curvature. After shape matching, the descriptors are submitted to statistical analysis to highlight the modes of variations within the samples. The obtained statistical model is the basis of the proposed applications
Ferrandiz, Sylvain. "Evaluation d'une mesure de similitude en classification supervisée : application à la préparation de données séquentielles." Phd thesis, Université de Caen, 2006. http://tel.archives-ouvertes.fr/tel-00123406.
Повний текст джерелаdu travail est consacrée à la construction et à la sélection des variables descriptives.
L'approche filtre univariée usuellement adoptée nécessite l'emploi d'une méthode
d'évaluation d'une variable. Nous considérons la question de l'évaluation supervisée d'une
variable séquentielle. Pour résoudre ce problème, nous montrons qu'il suffit de résoudre
un problème plus général : celui de l'évaluation supervisée d'une mesure de similitude.
Nous proposons une telle méthode d'évaluation. Pour l'obtenir, nous formulons le
problème en un problème de recherche d'une partition de Voronoi informative. Nous
proposons un nouveau critère d'évaluation supervisée de ces partitions et une nouvelle
heuristique de recherche optimisée. Le critère prévient automatiquement le risque de surapprentissage
et l'heuristique trouve rapidement une bonne solution. Au final, la méthode
réalise une estimation non paramétrique robuste de la densité d'une variable cible catégorielle
conditionnellement à une mesure de similitude définie à partir d'une variable descriptive.
La méthode a été testée sur de nombreux jeux de données. Son utilisation permet
de répondre à des questions comme : quel jour de la semaine ou quelle tranche horaire
sur la semaine discrimine le mieux le segment auquel appartient un foyer à partir de sa
consommation téléphonique fixe ? Quelle série de mesures permet de quantifier au mieux l'appétence à un nouveau service ?
Jin, Xiong. "Construction et analyse multifractale de fonctions aléatoires et de leurs graphes." Phd thesis, Université Paris Sud - Paris XI, 2010. http://tel.archives-ouvertes.fr/tel-00841501.
Повний текст джерелаDrira, Khalil. "Transformation et composition de graphes de refus : analyse de la testabilité." Toulouse 3, 1992. http://www.theses.fr/1992TOU30142.
Повний текст джерелаCapelle, Christian. "Décompositions de graphes et permutations factorisantes." Montpellier 2, 1997. http://www.theses.fr/1997MON20006.
Повний текст джерелаGay, Dominique. "Calcul de motifs sous contraintes pour la classification supervisée." Phd thesis, Université de Nouvelle Calédonie, 2009. http://tel.archives-ouvertes.fr/tel-00516706.
Повний текст джерелаRuiz, Dominguez Cinta. "Analyse automatique des troubles de contraction cardiaque en échocardiographie." Paris 11, 2005. http://www.theses.fr/2005PA112074.
Повний текст джерелаMany methods are developed to study the automatic evaluation of the left ventricle regional wall motion (normokinesia, hypokinesia, akinesia and dyskinesia), especially in echocardiography. A new parametric imaging method, based on the temporal intensity of pixels and called ‘parametric analysis of the main motion' (pamm) was proposed. This method synthesises the information contained in a sequence of images into two parametric images interpretable by a clinician: a three-color image of amplitude and a mean time contraction image. 602 segments of a database were scored with the interpretation of the pamm images and compared to a consensual visual interpretation of the cine-loop sequences by two experimented readers. Absolute and relative concordances are 64% and 82%. Some segmental indices were estimated from the pamm images. An automatic classification of the segments into two classes (normal and pathological segments) using this indices was performed. The diagnostic performance of the different indices was evaluated using the roc curve theory. Then a four-classes classification was done using the optimal index. Absolute and relative concordances obtained by the four-classes classification on a test database are 56% and 90%. The results could be improved if the localisation and the echogenicity of the segments are taken into account for the indices estimation
El, Maftouhi Abdelhakim. "Méthodes probabilistes en combinatoire et théorie des graphes." Paris 11, 1994. http://www.theses.fr/1994PA112408.
Повний текст джерелаRafi, Selwa. "Chaînes de Markov cachées et séparation non supervisée de sources." Thesis, Evry, Institut national des télécommunications, 2012. http://www.theses.fr/2012TELE0020/document.
Повний текст джерелаThe restoration problem is usually encountered in various domains and in particular in signal and image processing. It consists in retrieving original data from a set of observed ones. For multidimensional data, the problem can be solved using different approaches depending on the data structure, the transformation system and the noise. In this work, we have first tackled the problem in the case of discrete data and noisy model. In this context, the problem is similar to a segmentation problem. We have exploited Pairwise and Triplet Markov chain models, which generalize Hidden Markov chain models. The interest of these models consist in the possibility to generalize the computation procedure of the posterior probability, allowing one to perform bayesian segmentation. We have considered these methods for two-dimensional signals and we have applied the algorithms to retrieve of old hand-written document which have been scanned and are subject to show through effect. In the second part of this work, we have considered the restoration problem as a blind source separation problem. The well-known "Independent Component Analysis" (ICA) method requires the assumption that the sources be statistically independent. In practice, this condition is not always verified. Consequently, we have studied an extension of the ICA model in the case where the sources are not necessarily independent. We have introduced a latent process which controls the dependence and/or independence of the sources. The model that we propose combines a linear instantaneous mixing model similar to the one of ICA model and a probabilistic model on the sources with hidden variables. In this context, we show how the usual independence assumption can be weakened using the technique of Iterative Conditional Estimation to a conditional independence assumption
Lecomte, Sébastien. "Classification partiellement supervisée par SVM : application à la détection d’événements en surveillance audio." Thesis, Troyes, 2013. http://www.theses.fr/2013TROY0031/document.
Повний текст джерелаThis thesis addresses partially supervised Support Vector Machines for novelty detection (One-Class SVM). These have been studied to design abnormal audio events detection for supervision of public infrastructures, in particular public transportation systems. In this context, the null hypothesis (“normal” audio signals) is relatively well known (even though corresponding signals can be notably non stationary). Conversely, every “abnormal” signal should be detected and, if possible, clustered with similar signals. Thus, a reference system based on a single model of normal signals is presented, then we propose to use several concurrent One-Class SVM to cluster new data. Regarding the amount of data to process, special solvers have been studied. The proposed algorithms must be real time. This is the reason why we have also investigated algorithms with warm start capabilities. By the study of these algorithms, we have proposed a unified framework for One Class and Binary SVMs, with and without bias. The proposed approach has been validated on a database of real signals. The whole process applied to the monitoring of a subway station has been presented during the final review of the European Project VANAHEIM
Hidane, Moncef. "Décompositions multi-échelles de données définies sur des graphes." Caen, 2013. http://www.theses.fr/2013CAEN2088.
Повний текст джерелаThis thesis is concerned with approaches to the construction of multiscale decompositions of signals defined on general weighted graphs. This manuscript discusses three approaches that we have developed. The first approach is based on a variational and iterative process. It generalizes the structure-texture decomposition, originally proposed for images. Two versions are proposed: one is based on a quadratic prior while the other is based on a total variation prior. The study of the convergence is performed and the choice of parameters discussed in each case. We describe the application of the decompositions we get to the enhancement of details in images and 3D models. The second approach provides a multiresolution analysis of the space of signals on a given graph. This construction is based on the organization of the graph as a hierarchy of partitions. We have developed an adaptive algorithm for the construction of such hierarchies. Finally, in the third approach, we adapt the lifting scheme to signals on graphs. This adaptation raises a number of practical problems. We focused on the one hand on the subsampling step for which we adopted a greedy approach, and on the other hand on the iteration of the transform on induced subgraphs
Delanoue, Nicolas. "Algorithmes numériques pour l'analyse topologique : Analyse par intervalles et théorie des graphes." Phd thesis, Université d'Angers, 2006. http://tel.archives-ouvertes.fr/tel-00340999.
Повний текст джерелаDe nombreux problèmes, comme l'étude de l'espace des configurations d'un robot, se ramènent à une étude qualitative d'ensembles. Ici, la ``taille'' de l'ensemble importe peu, ce qui compte, c'est sa ``topologie''. Les méthodes proposées calculent des invariants topologiques d'ensembles. Les ensembles considérés sont décrits à l'aide d'inégalités $\mathcal{C}^{\infty}$. L'idée maîtresse est de décomposer un ensemble donné en parties contractiles et d'utiliser l'homologie de \v Cech.
La seconde partie de la thèse concerne l'étude de point
asymptotiquement stables des systèmes dynamiques (linéaires ou non). Plus largement, on propose une méthode pour approcher le bassin d'attraction d'un point asymptotiquement stable. Dans un premier temps, on utilise la théorie de Lyapunov et le calcul par intervalle
pour trouver effectivement un voisinage inclus dans le bassin d'attraction d'un point prouvé asymptotiquement stable. Puis, on combine, une fois de plus, la théorie des graphes et les méthodes d'intégration d'équations différentielles ordinaires pour améliorer ce voisinage et ainsi construire un ensemble inclus dans le bassin
d'attraction de ce point.
VENET, ARNAUD. "Analyse statique des systemes dynamiques de graphes dans les langages non types." Palaiseau, Ecole polytechnique, 1998. http://www.theses.fr/1998EPXX0073.
Повний текст джерелаTanana, Mariam. "Evaluation formative du savoir-faire des apprenants à l'aide d'algorithmes de classification : application à l'électronique numérique." Phd thesis, INSA de Rouen, 2009. http://tel.archives-ouvertes.fr/tel-00442930.
Повний текст джерелаKalakech, Mariam. "Sélection semi-supervisée d'attributs : application à la classification de textures couleur." Thesis, Lille 1, 2011. http://www.theses.fr/2011LIL10018/document.
Повний текст джерелаWithin the framework of this thesis, we are interested in feature selection methods based on graph theory in different unsupervised, semi-supervised and supervised learning contexts. We are particularly interested in the feature ranking scores based on must-link et cannot-link constraints. Indeed, these constraints are easy to be obtained on real applications. They just require to formalize for two data samples if they are similar and then must be grouped together or not, without detailed information on the classes to be found. Constraint scores have shown good performances for semi-supervised feature selection. However, these scores strongly depend on the given must-link and cannot-link subsets built by the user. We propose then a new semi-supervised constraint scores that uses both pairwise constraints and local properties of the unconstrained data. Experiments on artificial and real databases show that this new score is less sensitive to the given constraints than the previous scores while providing similar performances. Semi supervised feature selection was also successfully applied to the color texture classification. Indeed, among many texture features which can be extracted from the color images, it is necessary to select the most relevant ones to improve the quality of classification
RAFI, Selwa. "Chaînes de Markov cachées et séparation non supervisée de sources." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00995414.
Повний текст джерелаGrebinski, Vladimir. "Recherche combinatoire : problèmes de pesage, reconstruction de graphes et applications." Nancy 1, 1998. http://www.theses.fr/1998NAN10248.
Повний текст джерелаSeifi, Massoud. "Coeurs stables de communautés dans les graphes de terrain." Paris 6, 2012. http://www.theses.fr/2012PA066058.
Повний текст джерелаIn many contexts, sets of related entities can be modeled by graphs, in which entities are represented by nodes and relationships between these entities by edges. These graphs, which we call "complex networks", may be encountered in the real world in various fields such as social science, computer science, biology, transportation, linguistics, etc. Most complex networks are composed of dense subgraphs weakly interconnected called "communities" and many algorithms have been proposed to identify the community structure of complex networks automatically. During this thesis, we focused on the problems of community detection algorithms, especially their non-determinism and the instability that results. We presented a methodology that takes advantage of this non-determinism to improve the results obtained with current community detection techniques. We proposed an approach based on the concept of strong communities, or "community cores", and we showed the improvement made by our approach by applying it to real and artificial graphs. We also studied the structure of cores in random graphs and we showed that unlike classical community detection algorithms which can find communities in graphs with no intrinsic community structure, our approach clearly indicates the absence of community structure in random graphs and, in this way, allows to distinguish between random and real graphs. We also studied the evolution of cores in dynamical networks using a simple and controllable simulated dynamic and a real dynamic. We showed that cores are much more stable than communities obtained by current community detection techniques and our approach can overcome the disadvantages of stabilized methods that have been recently proposed
Golenia, Sylvain. "Méthodes algébriques dans l'analyse spectrale d'opérateurs sur les graphes et les variétés." Cergy-Pontoise, 2004. http://biblioweb.u-cergy.fr/theses/04CERG0218.PDF.
Повний текст джерелаIn this thesis, we use C-star-algebraical techniques aiming for applications in spectral theory. In the first two articles, in the context of trees, we adapt the C-star-algebra methods to the study of the spectral and scattering theories of Hamiltonians of the system. We first consider a natural formulation and generalization of the problem in a Fock space context. We then get a Mourre estimate for the free Hamiltonian and its perturbations. Finally, we compute the quotient of a C-star-algebra of energy observables with respect to its ideal of compact operators. As an application, the essential spectrum of highly anisotropic Schr\"odinger operators is computed. In the third article, we give powerful critera of stability of the essential spectrum of unbounded operators. Our applications cover Dirac operators, perturbations of riemannian metrics, differential operators in divergence form. The main point of our approach is that no regularity conditions are imposed on the coefficients
Golenia, Sylvain Georgescu Vladimir. "Méthodes algébriques dans l'analyse spectrale d'opérateurs sur les graphes et les variétés." [s.l.] : [s.n.], 2007. http://biblioweb.u-cergy.fr/theses/04CERG0218.PDF.
Повний текст джерелаBarakat-Barbieri, Bruno. "Vers une construction automatique de graphes de concepts." Châtenay-Malabry, Ecole centrale de Paris, 1992. http://www.theses.fr/1992ECAP0416.
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