Gotowa bibliografia na temat „Appariement des objets”
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Rozprawy doktorskie na temat "Appariement des objets"
Auxepaules, Ludovic. "Analyse des diagrammes de l'apprenant dans un EIAH pour la modélisation orientée objet - Le système ACDC". Phd thesis, Université du Maine, 2009. http://tel.archives-ouvertes.fr/tel-00455992.
Pełny tekst źródłaLebrun, Justine. "Appariement inexact de graphes appliqué à la recherche d'images et d'objets 3D". Thesis, Cergy-Pontoise, 2011. http://www.theses.fr/2011CERG0510/document.
Pełny tekst źródłaMany type of documents can be modeled by a graph representation. In this thesis, we focus on theuse of graph for research in multimedia databases.We begin by presenting the theory of graphs and aroundan overview of methods that have been proposed for matching.Then, we are particularly interested in their use for recognitionforms and multimedia indexing.In order to respond in the most generic possible differentresearch problems, we propose to work within the framework of kernel functions.This framework allows to separate the problems related to the nature of the documentsthose introduced by the different types of research. Thus, all ourenergy is devoted to the design of mapping functions,but bearing in mind that they must meet a numbermathematical properties. In this context, we propose newsolutions that better meet the specificgraphs from primitive and visual descriptors. Wealso present algorithms to quickly assessthese functions. Finally, wepresent experiments that highlight thesedifferent characteristics and experiences that showadvantages of our models with respect to the literature
Saada, Hajer. "Exploiting Model Transformation Examples for Easy Model Transformation Handling (Learning and Recovery)". Thesis, Montpellier 2, 2013. http://www.theses.fr/2013MON20223/document.
Pełny tekst źródłaModel Driven Engineering (MDE) considers models as first class artifacts. Each model conforms to another model, called its metamodel which defines its abstract syntax and its semantics.Various kinds of models are handled successively in an MDE development cycle. They are manipulated using, among others, programs called model transformations. A transformation takes as input a model in a source language and produces a model in a target language. The developers of a transformation must have a strong knowledge about the source and target metamodels which are involved and about the model transformation language. This makes the writing of the model transformation difficult.In this thesis, we address the problem of assisting the writing of a model transformation and more generally of understanding how a transformation operates.We adhere to the Model Transformation By example (MTBE) approach, which proposes to create a model transformation using examples of transformation. MTBE allows us to use the concrete syntaxes defined for the metamodels. Hence, the developers do not need in-depth knowledge about the metamodels. In this context, our thesis proposes two contributions.As a first contribution, we define a method to generate operational transformation rules from transformation examples. We extend a previous approach which uses Relational Concept Analysis as a learning technique for obtaining transformation patterns from 1-1 mapping between models. We develop a technique for extracting relevant transformation rules from these transformation patterns and we use JESS language and engine to make the rules executable. We also study how we better learn transformation rules from examples, using transformation examples separately or by gathering all the examples.The second contribution consists in recovering transformation traces from transformation examples. This trace recovery is useful for several purposes as locating bugs during the execution of transformation programs, or checking the coverage of all input models by a transformation. In our context, we expect also that this trace will provide data for a future model transformation learning technique. We first address the trace recovery problem with examples coming from a transformation program. We propose an approach, based on a multi-objective meta-heuristic, to generate the textit{many-to-many} mapping between model constructs which correspond to a trace. The fitness functions rely on the lexical and structure similarity between the constructs. We also refine the approach to apply it to the more general problem of model matching
Devogele, Thomas. "Système d'information géographique temporelle maritime ; Des distances linéaires à l'analyse temps réel des trajectoires". Habilitation à diriger des recherches, Université de Bretagne occidentale - Brest, 2009. http://tel.archives-ouvertes.fr/tel-00441484.
Pełny tekst źródłaDuchenne, Olivier. "Non-rigid image alignment for object recognition". Phd thesis, École normale supérieure de Cachan - ENS Cachan, 2012. http://tel.archives-ouvertes.fr/tel-00906074.
Pełny tekst źródłaRevaud, Jérôme. "Contributions to a fast and robust object recognition in images". Phd thesis, INSA de Lyon, 2011. http://tel.archives-ouvertes.fr/tel-00694442.
Pełny tekst źródłaQuidu, Isabelle. "Classification multi-vues d'un objet immergé à partir d'images sonar et de son ombre portée sur le fond". Phd thesis, Université de Bretagne occidentale - Brest, 2001. http://tel.archives-ouvertes.fr/tel-00504902.
Pełny tekst źródłaBursuc, Andrei. "Indexation et recherche de contenus par objet visuel". Phd thesis, Ecole Nationale Supérieure des Mines de Paris, 2012. http://pastel.archives-ouvertes.fr/pastel-00873966.
Pełny tekst źródłaMadi, Kamel. "Inexact graph matching : application to 2D and 3D Pattern Recognition". Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1315/document.
Pełny tekst źródłaGraphs are powerful mathematical modeling tools used in various fields of computer science, in particular, in Pattern Recognition. Graph matching is the main operation in Pattern Recognition using graph-based approach. Finding solutions to the problem of graph matching that ensure optimality in terms of accuracy and time complexity is a difficult research challenge and a topical issue. In this thesis, we investigate the resolution of this problem in two fields: 2D and 3D Pattern Recognition. Firstly, we address the problem of geometric graphs matching and its applications on 2D Pattern Recognition. Kite (archaeological structures) recognition in satellite images is the main application considered in this first part. We present a complete graph based framework for Kite recognition on satellite images. We propose mainly two contributions. The first one is an automatic process transforming Kites from real images into graphs and a process of generating randomly synthetic Kite graphs. This allowing to construct a benchmark of Kite graphs (real and synthetic) structured in different level of deformations. The second contribution in this part, is the proposition of a new graph similarity measure adapted to geometric graphs and consequently for Kite graphs. The proposed approach combines graph invariants with a geometric graph edit distance computation. Secondly, we address the problem of deformable 3D objects recognition, represented by graphs, i.e., triangular tessellations. We propose a new decomposition of triangular tessellations into a set of substructures that we call triangle-stars. Based on this new decomposition, we propose a new algorithm of graph matching to measure the distance between triangular tessellations. The proposed algorithm offers a better measure by assuring a minimum number of triangle-stars covering a larger neighbourhood, and uses a set of descriptors which are invariant or at least oblivious under most common deformations. Finally, we propose a more general graph matching approach founded on a new formalization based on the stable marriage problem. The proposed approach is optimal in term of execution time, i.e. the time complexity is quadratic O(n2) and flexible in term of applicability (2D and 3D). The analyze of the time complexity of the proposed algorithms and the extensive experiments conducted on Kite graph data sets (real and synthetic) and standard data sets (2D and 3D) attest the effectiveness, the high performance and accuracy of the proposed approaches and show that the proposed approaches are extensible and quite general