Conception d'un dispositif d'acquisition d'images agronomiques 3D en extérieur et développement des traitements associés pour la détection et la reconnaissance de plantes et de maladies

Dans le cadre de l'acquisition de l'information de profondeur de scènes texturées, un processus d'estimation de la profondeur basé sur la méthode de reconstruction 3D Shape from Focus est présenté dans ce manuscrit. Les deux étapes fondamentales de cette approche sont l'acquisition de la séquence d'images de la scène par sectionnement optique et l'évaluation de la netteté locale pour chaque pixel des images acquises. Deux systèmes d'acquisition de cette séquence d'images sont présentés ainsi que les traitements permettant d'exploiter celle-ci pour la suite du processus d'estimation de la profondeur. L'étape d'évaluation de la netteté des pixels passe par la comparaison des différents opérateurs de mesure de netteté. En plus des opérateurs usuels, deux nouveaux opérateurs basés sur les descripteurs généralisés de Fourier sont proposés. Une méthode nouvelle et originale de comparaison est développée et permet une analyse approfondie de la robustesse à différents paramètres des divers opérateurs. Afin de proposer une automatisation du processus de reconstruction, deux méthodes d'évaluation automatique de la netteté sont détaillées. Finalement, le processus complet de reconstruction est appliqué à des scènes agronomiques, mais également à une problématique du domaine de l'analyse de défaillances de circuits intégrés afin d'élargir les domaines d'utilisationIn the context of the acquisition of depth information for textured scenes, a depth estimation process based on a 3D reconstruction method called "shape from focus" is proposed in this thesis. The two crucial steps of this approach are the image sequence acquisition of the scene by optical sectioning and the local sharpness evaluation for each pixel of the acquired images. Two acquisition systems have been developed and are presented as well as different image processing techniques that enable the image exploitation for the depth estimation process. The pixel sharpness evaluation requires comparison of different focus measure operators in order to determine the most appropriate ones. In addition to the usual focus measure operators, two news operators based on generalized Fourier descriptors are presented. A new and original comparison method is developped and provides a further analysis of the robustness to various parameters of the focus measure operators. In order to provide an automatic version of the reconstruction process, two automatic sharpness evaluation methods are detailed. Finally, the whole reconstruction process is applied to agronomic scenes, but also to a problematic in failure analysis domain aiming to expand to other applicationsDIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

An Analytical Study of Large SPARQL Query Logs

With the adoption of RDF as the data model for Linked Data and the Semantic Web, query specification from end- users has become more and more common in SPARQL end- points. In this paper, we conduct an in-depth analytical study of the queries formulated by end-users and harvested from large and up-to-date query logs from a wide variety of RDF data sources. As opposed to previous studies, ours is the first assessment on a voluminous query corpus, span- ning over several years and covering many representative SPARQL endpoints. Apart from the syntactical structure of the queries, that exhibits already interesting results on this generalized corpus, we drill deeper in the structural char- acteristics related to the graph- and hypergraph represen- tation of queries. We outline the most common shapes of queries when visually displayed as pseudographs, and char- acterize their (hyper-)tree width. Moreover, we analyze the evolution of queries over time, by introducing the novel con- cept of a streak, i.e., a sequence of queries that appear as subsequent modifications of a seed query. Our study offers several fresh insights on the already rich query features of real SPARQL queries formulated by real users, and brings us to draw a number of conclusions and pinpoint future di- rections for SPARQL query evaluation, query optimization, tuning, and benchmarking

Spectral limits of semiclassical commuting self-adjoint operators

Using an abstract notion of semiclassical quantization for self-adjoint operators, we prove that the joint spectrum of a collection of commuting semiclassical self-adjoint operators converges to the classical spectrum given by the joint image of the principal symbols, in the semiclassical limit. This includes Berezin-Toeplitz quantization and certain cases of $\hbar$-pseudodifferential quantization, for instance when the symbols are uniformly bounded, and extends a result by L. Polterovich and the authors. In the last part of the paper we review the recent solution to the inverse problem for quantum integrable systems with periodic Hamiltonians, and explain how it also follows from the main result in this paper.Comment: 19 pages, 2 figures. To appear in volume in honor of J.M. Montesinos Amilibi

Probing Galaxy Dark Matter Haloes in COSMOS with Weak Lensing Flexion

Current theories of structure formation predict specific density profiles of galaxy dark matter haloes, and with weak gravitational lensing we can probe these profiles on several scales. On small scales, higher-order shape distortions known as flexion add significant detail to the weak lensing measurements. We present here the first detection of a galaxy-galaxy flexion signal in space-based data, obtained using a new Shapelets pipeline introduced here. We combine this higher-order lensing signal with shear to constrain the average density profile of the galaxy lenses in the Hubble Space Telescope COSMOS survey. We also show that light from nearby bright objects can significantly affect flexion measurements. After correcting for the influence of lens light, we show that the inclusion of flexion provides tighter constraints on density profiles than does shear alone. Finally we find an average density profile consistent with an isothermal sphere.Comment: 14 pages, 14 figures. Accepted for publication in MNRA

How Supervisors Influence Performance: A Multilevel Study of Coaching and Group Management in Technology-Mediated Services

This multilevel study examines the role of supervisors in improving employee performance through the use of coaching and group management practices. It examines the individual and synergistic effects of these management practices. The research subjects are call center agents in highly standardized jobs, and the organizational context is one in which calls, or task assignments, are randomly distributed via automated technology, providing a quasi-experimental approach in a real-world context. Results show that the amount of coaching that an employee received each month predicted objective performance improvements over time. Moreover, workers exhibited higher performance where their supervisor emphasized group assignments and group incentives and where technology was more automated. Finally, the positive relationship between coaching and performance was stronger where supervisors made greater use of group incentives, where technology was less automated, and where technological changes were less frequent. Implications and potential limitations of the present study are discussed

A survey of uncertainty principles and some signal processing applications

The goal of this paper is to review the main trends in the domain of uncertainty principles and localization, emphasize their mutual connections and investigate practical consequences. The discussion is strongly oriented towards, and motivated by signal processing problems, from which significant advances have been made recently. Relations with sparse approximation and coding problems are emphasized