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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
11

Intergiciel agent pour le déploiement et la configuration d'applications distribuées dans des environnements ambiants / An agent middleware for the deployment and the configuration of distributed applications in ambient environments

Piette, Ferdinand 17 January 2017 (has links)
L'évolution des technologies de l'information ainsi que la miniaturisation constante des composants électroniques de ces dernières décennies ont permis de doter les objets de la vie de tous les jours de capacités de calcul et de communication. Ces objets connectés sont disséminés dans l'environnement de l'utilisateur et coopèrent les uns avec les autres afin de fournir à l'utilisateur des services intelligents de manière totalement transparente et non intrusive. Ces environnements sont caractérisés par une grande hétérogénéité ainsi qu'une grande dynamicité. Les intégrations dites verticales (les données des capteurs sont externalisées sur les serveurs d'une entreprise) permettent certes une interopérabilité plus importante, mais engendrent des problèmes de saturation des canaux de communication, ainsi que des questionnements sur la sécurité et la confidentialité de des informations. Pour pallier ces problèmes, les intégrations dites horizontales (les entités matérielles sont mises en relation directement au sein de l'infrastructure) sont encouragées. Dans cette thèse, nous adressons le problème du déploiement et de la configuration automatique d'applications au sein de tels environnements ambiants. Nous proposons des mécanismes permettant, à partir d'une description de l'environnement ambiant, la sélection et la configuration d'entités matérielles qui supporteront l'exécution des applications. Ces mécanismes ont été encapsulé dans un intergiciel basé sur le paradigme Multi-agents dans lequel les différents agents logiciels du système collaborent afin de sélectionner les entités de l'infrastructure respectant les besoins et les contraintes des applications à déployer. / Research domains like Ambient Intelligence or Internet of Things came up in the early 2000’s with the technologic improvement and the ongoing miniaturization of electronic devices. These electronic and information devices are scattered in the user’s environment, can communicate and exchange data more and more easily to provide intelligent and non-intrusive services to the users. However, it is difficult to have generic implementations of these applications. These difficulties are due the the high heterogeneity and dynamicity of the ambient environments. Vertical integrations of connected devices (data exchanges from the devices to external servers) allow more interoperability but generate overloads of the communication channels and privacy concerns. To prevent these problems, horizontal approaches (connected devices communicate directly together through the hardware infrastructure) have to be encouraged. In this thesis work, we address the problem of the automatic deployment and configuration of distributed applications in these ambient environments. We propose mechanisms that allow, from a description of the environment, the selection and the configuraion of the hardware entities that will support the execution of applications. These mechanisms are encapsulated in a middleware based on the multi-agent paradigm. The different agents of the system cooperate in order to select the right hardware entities that respects the requirements and the constraints of the applications we want to deploy.
12

A Methodology for the Integration of Hopfield Network and Genetic Algorithm Schemes for Graph Matching Problems

Huang, Chin-Chung 14 February 2005 (has links)
Object recognition is of much interest in recent industrial automation. Although a variety of approaches have been proposed to tackle the recognition problem, some cases such as overlapping objects, articulated objects, and low-resolution images, are still not easy for the existing schemes. Coping with these more complex images has remained a challenging task in the field. This dissertation, aiming to recognize objects from such images, proposes a new integrated method. For images with overlapping or articulated objects, graph matching methods are often used, seeing them as solving a combinatorial optimization problem. Both Hopfield network and the genetic algorithm are decent tools for the combinatorial optimization problems. Unfortunately, they both have intolerable drawbacks. The Hopfield network is sensitive to its initial state and stops at a local minimum if it is not properly given. The GA, on the other hand, only finds a near-global solution, and it is time-consuming for large-scale tasks. This dissertation proposes to combine these two methods, while eliminating their bad and keeping their good, to solve some complex recognition problems. Before the integration, some arrangements are required. For instance, specialized 2-D GA operators are used to accelerate the convergence. Also, the ¡§seeds¡¨ of the solution of the GA is extracted as the initial state of the Hopfield network. By doing so the efficiency of the system is greatly improved. Additionally, several fine-tuning post matching algorithms are also needed. In order to solve the homomorphic graph matching problem, i.e., multiple occurrences in a single scene image, the Hopfield network has to repeat itself until the stopping criteria are met. The method can not only be used to obtain the homomorphic mapping between the model and the scene graphs, but it can also be applied to articulated object recognition. Here we do not need to know in advance if the model is really an articulated object. The proposed method has been applied to measure some kinematic properties, such as the positions of the joints, relative linear and angular displacements, of some simple machines. The subject about articulated object recognition has rarely been mentioned in the literature, particularly under affine transformations. Another unique application of the proposed method is also included in the dissertation. It is about using low-resolution images, where the contour of an object is easily affected by noise. To increase the performance, we use the hexagonal grid in dealing with such low-resolution images. A hexagonal FFT simulation is first presented to pre-process the hexagonal images for recognition. A feature vector matching scheme and a similarity matching scheme are also devised to recognize simpler images with only isolated objects. For complex low-resolution images with occluded objects, the integrated method has to be tailored to go with the hexagonal grid. The low-resolution, hexagonal version of the integrated scheme has also been shown to be suitable and robust.
13

Contributions to a fast and robust object recognition in images

Revaud, Jérôme 27 May 2011 (has links) (PDF)
In this thesis, we first present a contribution to overcome this problem of robustness for the recognition of object instances, then we straightly extend this contribution to the detection and localization of classes of objects. In a first step, we have developed a method inspired by graph matching to address the problem of fast recognition of instances of specific objects in noisy conditions. This method allows to easily combine any types of local features (eg contours, textures ...) less affected by noise than keypoints, while bypassing the normalization problem and without penalizing too much the detection speed. Unlike other methods based on a global rigid transformation, our approach is robust to complex deformations such as those due to perspective or those non-rigid inherent to the model itself (e.g. a face, a flexible magazine). Our experiments on several datasets have showed the relevance of our approach. It is overall slightly less robust to occlusion than existing approaches, but it produces better performances in noisy conditions. In a second step, we have developed an approach for detecting classes of objects in the same spirit as the bag-of-visual-words model. For this we use our cascaded micro-classifiers to recognize visual words more distinctive than the classical words simply based on visual dictionaries. Training is divided into two parts: First, we generate cascades of micro-classifiers for recognizing local parts of the model pictures and then in a second step, we use a classifier to model the decision boundary between images of class and those of non-class. We show that the association of classical visual words (from keypoints patches) and our disctinctive words results in a significant improvement. The computation time is generally quite low, given the structure of the cascades that minimizes the detection time and the form of the classifier is extremely fast to evaluate.
14

Spatial, Temporal and Spatio-Temporal Correspondence for Computer Vision Problems

Zhou, Feng 01 September 2014 (has links)
Many computer vision problems, such as object classification, motion estimation or shape registration rely on solving the correspondence problem. Existing algorithms to solve spatial or temporal correspondence problems are usually NP-hard, difficult to approximate, lack flexible models and mechanism for feature weighting. This proposal addresses the correspondence problem in computer vision, and proposes two new spatio-temporal correspondence problems and three algorithms to solve spatial, temporal and spatio-temporal matching between video and other sources. The main contributions of the thesis are: (1) Factorial graph matching (FGM). FGM extends existing work on graph matching (GM) by finding an exact factorization of the affinity matrix. Four are the benefits that follow from this factorization: (a) There is no need to compute the costly (in space and time) pairwise affinity matrix; (b) It provides a unified framework that reveals commonalities and differences between GM methods. Moreover, the factorization provides a clean connection with other matching algorithms such as iterative closest point; (c) The factorization allows the use of a path-following optimization algorithm, that leads to improved optimization strategies and matching performance; (d) Given the factorization, it becomes straight-forward to incorporate geometric transformations (rigid and non-rigid) to the GM problem. (2) Canonical time warping (CTW). CTW is a technique to temporally align multiple multi-dimensional and multi-modal time series. CTW extends DTW by incorporating a feature weighting layer to adapt different modalities, allowing a more flexible warping as combination of monotonic functions, and has linear complexity (unlike DTW that has quadratic). We applied CTW to align human motion captured with different sensors (e.g., audio, video, accelerometers). (3) Spatio-temporal matching (STM). Given a video and a 3D motion capture model, STM finds the correspondence between subsets of video trajectories and the motion capture model. STM is efficiently and robustly solved using linear programming. We illustrate the performance of STM on the problem of human detection in video, and show how STM achieves state-of-the-art performance.
15

Non-rigid image alignment for object recognition / Alignement élastique d’images pour la reconnaissance d’objet

Duchenne, Olivier 29 November 2012 (has links)
La vision permet aux animaux de recueillir une information riche et détaillée sur leur environnent proche ou lointain. Les machines ont aussi accès à cette information riche via leurs caméras. Mais, elles n'ont pas encore le logiciel adéquat leur permettant de la traiter pour transformer les valeurs brutes des pixels de l'image en information plus utile telle que la nature, la position, et la fonction des objets environnants. Voilà une des raisons pour laquelle il leur est difficile de se mouvoir dans un environnement inconnu, et d'interagir avec les humains ou du matériel dans des scénarios non-planifiés. Cependant, la conception de ce logiciel comporte de multiples défis. Parmi ceux-ci, il est difficile de comparer deux images entre elles, par exemple, afin que la machine puisse reconnaître que ce qu'elle voit est similaire à une image qu'elle a déjà vue et identifiée. Une des raisons de cette difficulté est que la machine ne sait pas, a priori, quelles parties des deux images se correspondent, et ne sait donc pas quoi comparer avec quoi. Cette thèse s'attaque à ce problème et propose une série d'algorithmes permettant de trouver les parties correspondantes entre plusieurs images, ou en d'autre terme d'aligner les images. La première méthode proposée permet d'apparier ces parties de manière cohérente en prenant en compte les interactions entre plus de deux d'entre elles. Le deuxième algorithme proposé applique avec succès une méthode d'alignement pour déterminer la catégorie d'un objet centré dans une image. Le troisième est optimisé pour la vitesse et tente de détecter un objet d'une catégorie donné où qu'il soit dans l'image. / Seeing allows animals and people alike to gather information from a distance, often with high spatial and temporal resolution. Machines have access to this rich pool of information thanks to their cameras. But, they still do not have the software to process it, in order to transform the raw pixel values into useful information such as nature, position, and function of the surrounding objects. That is one of the reasons why it is still difficult for them to naviguate in an unknown environment and interract with people and objects in an un-planned fashion. However, the design of such a software implies many challenges. Among them, it is hard to compare two images, for insance, in order to recognize that the seen image is similar to another which has been previously seen and identified. One of the difficulties here is that the software cannot know --a priori-- which parts of the two images match. So, it cannot know which parts it should compare. This thesis tackles that problem, and presents a set of algorithm to find correspondences in images, or in other words, to align them. The first proposed method match parts in images, in a coherent fachion, taking into account higher order interactions between more than to of them. The second proposed algorithm apply with success alignment technique to discover the category of an object centered in an image. The third one is optimized for speed and try to detect objects of a given category, which can be anywhere in an image.
16

A survey of approaches to automatic schema matching

Rahm, Erhard, Bernstein, Philip A. 19 October 2018 (has links)
Schema matching is a basic problem in many database application domains, such as data integration, E-business, data warehousing, and semantic query processing. In current implementations, schema matching is typically performed manually, which has significant limitations. On the other hand, previous research papers have proposed many techniques to achieve a partial automation of the match operation for specific application domains. We present a taxonomy that covers many of these existing approaches, and we describe the approaches in some detail. In particular, we distinguish between schema-level and instance-level, element-level and structure-level, and language-based and constraint-based matchers. Based on our classification we review some previous match implementations thereby indicating which part of the solution space they cover. We intend our taxonomy and review of past work to be useful when comparing different approaches to schema matching, when developing a new match algorithm, and when implementing a schema matching component.
17

Enhancing Productivity with Back-End Similarity Matching of Digital Circuits for IP Reuse

Zeng, Kevin 04 June 2013 (has links)
Productivity for digital circuit design is being outpaced currently by the rate at which<br />silicon is growing such as FPGAs. Complex designs take a large amount of engineering<br />hours to complete. Reuse of existing design can potentially decrease this cost and increase<br />design productivity. However, existing digital hardware designs are not being effectively<br />reused by the hardware community due to the inability of designers to have knowledge of<br />all the attributes of designs that can be reused. In addition, designers will have to accustom<br />themselves to designs in the hardware library. By having a back-end system that looks for<br />similar circuits, there is little to no effort for the designer to reuse the design. This thesis<br />provides an overview and comparison of different methods for characterizing and comparing<br />digital circuits in order to suggest candidate circuits that engineers can reuse. Several of<br />these methods are implemented, modified, and compared to show the feasibility of utilizing<br />this work for increasing overall productivity.<br /> / Master of Science
18

RoleSim and RoleMatch: Role-Based Similarity and Graph Matching

Lee, Victor Eugene 26 September 2012 (has links)
No description available.
19

Mutually Exclusive Weighted Graph Matching Algorithm for Protein-Protein Interaction Network Alignment

Dunham, Brandan 20 October 2016 (has links)
No description available.
20

Approches anytime et distribuées pour l'appariment de graphes / Anytime and distributed approaches for graph matching

Abu-Aisheh, Zeina 25 May 2016 (has links)
En raison de la capacité et de l'amélioration des performances informatiques, les représentations structurelles sont devenues de plus en plus populaires dans le domaine de la reconnaissance de formes (RF). Quand les objets sont structurés à base de graphes, le problme de la comparaison d'objets revient à un problme d'appariement de graphes (Graph Matching). Au cours de la dernière décennie, les chercheurs travaillant dans le domaine de l'appariement de graphes ont porté une attention particulière à la distance d'édition entre graphes (GED), notamment pour sa capacité à traiter différent types de graphes. GED a été ainsi appliquée sur des problématiques spécifiques qui varient de la reconnaissance de molécules à la classi fication d'images. / Due to the inherent genericity of graph-based representations, and thanks to the improvement of computer capacities, structural representations have become more and more popular in the field of Pattern Recognition (PR). In a graph-based representation, vertices and their attributes describe objects (or part of them) while edges represent interrelationships between the objects. Representing objects by graphs turns the problem of object comparison into graph matching (GM) where correspondences between vertices and edges of two graphs have to be found.

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