956 resultados para second pre-image attack
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Comprend : [Frontispice : Pape, moine, personnification de l'Eglise. Armoiries. XVIè siècle.] [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.90 : élévation d'une croix pour la bénédiction de l'Ile de Maragnan. XVIIè siècle.] [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.348 : indigène de l'Ile de Maragnan, nommé François Carypyra, de la tribu des Tabaiares. XVIIè siècle.] François Carypyra. [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.356 : indigène de l'Ile de Maragnan, nommé Jacques Patova. XVIIè siècle.] Jacques Patova. [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.359 : indigène de l'Ile de Maragnan, nommé Antoine Manen, natif de Renary, originaire de Para de l'Ouest. XVIIè siècle.] Anthoine Manen. [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.362 : indigène de l'Ile de Maragnan, nommé Itapoucou Topinamba et baptisé Louis-Marie. XVIIè siècle.] Louis Marie. [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.364 : indigène de l'Ile de Maragnan, nommé Ouäroyio Topinamba et baptisé Louis-Henry. XVIIè siècle.] Louis Henri. [cote : microfilm m 10858/R 15836] ; [pl. en reg. p.365 : indigène de l'Ile de Maragnan, nommé Iapouäy et baptisé Louis de Saint-Jean. XVIIè siècle.] Louis de St. Iehan. [cote : microfilm m 10858/R 15836]
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Comprend : [ Folios A1v ° et A2r °. Vue des deux cartes en couleur de l'hémisphère Européen-Africain et de l'hémisphère Américain. XVIè siècle.] [ Cote : BNF RCB 8010. ]
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Comprend : [Bandeau et lettrine au Prologue de l'auteur p.2 : le maître et son disciple] [Cote : microfilm R 18678] ; [Bandeau au chap. I en reg. p.6 :] De la généalogie et antiquité de Gargantua. [L'auteur rédigeant les chroniques pantagruelines.] [Cote : microfilm R 18678]
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Comprend : [Pl. en reg. p.46 :] Goriot mangeait machinalement. Jamais il n'avait semblé plus absorbé. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.78 :] "Madame, je ne suis encore qu'un pauvre diable d'étudiant..." dit Eugène à la duchesse. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.107 :] "Expliquons-nous..." dit Vautrin en prenant Eugène par le bras. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.133 :] Le marquis présenta l'étudiant à Mme Nucingen... [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.146 :] En sortant du cours Cuvier, Bianchon aperçut Mlle Michonneau et Poiret causant avec un monsieur qu'il sembla reconaître... [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.151 :] "Suis-je à votre goût?..." dit Mme de Nucingen en se levant et montrant sa robe de cachemire blanc à dessins. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.229 :] Mme de Nucingen se jeta dans les bras de son père, et couvrit de baisers son visage épanoui... [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.254 :] Le Père Goriot s'élança entre ses deux filles pour les embpêcher de continuer cet échange de reproches. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.272 :] "Je tremblais que vous ne vinssiez pas..." dit Mme de Beauséant à Rastignac. [Cote : Res p Y2 159/Microfilm R 122341] ; [Pl. en reg. p.300 :] "Mon père est mort!... " cria la comtesse en tombant évanouie. [Cote : Res p Y2 159/Microfilm R 122341]
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Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.
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Référence bibliographique : Weigert, 629
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We present MBIS (Multivariate Bayesian Image Segmentation tool), a clustering tool based on the mixture of multivariate normal distributions model. MBIS supports multichannel bias field correction based on a B-spline model. A second methodological novelty is the inclusion of graph-cuts optimization for the stationary anisotropic hidden Markov random field model. Along with MBIS, we release an evaluation framework that contains three different experiments on multi-site data. We first validate the accuracy of segmentation and the estimated bias field for each channel. MBIS outperforms a widely used segmentation tool in a cross-comparison evaluation. The second experiment demonstrates the robustness of results on atlas-free segmentation of two image sets from scan-rescan protocols on 21 healthy subjects. Multivariate segmentation is more replicable than the monospectral counterpart on T1-weighted images. Finally, we provide a third experiment to illustrate how MBIS can be used in a large-scale study of tissue volume change with increasing age in 584 healthy subjects. This last result is meaningful as multivariate segmentation performs robustly without the need for prior knowledge.
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Référence bibliographique : Weigert, 401
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This research project investigated the use of image analysis to measure the air void parameters of concrete specimens produced under standard laboratory conditions. The results obtained from the image analysis technique were compared to results obtained from plastic air content tests, Danish air meter tests (also referred to as Air Void Analyzer tests), high-pressure air content tests on hardened concrete, and linear traverse tests (as per ASTM C-457). Hardened concrete specimens were sent to three different laboratories for the linear traverse tests. The samples that were circulated to the three labs consisted of specimens that needed different levels of surface preparation. The first set consisted of approximately 18 specimens that had been sectioned from a 4 in. by 4 in. by 18 in. (10 cm by 10 cm by 46 cm) beam using a saw equipped with a diamond blade. These specimens were subjected to the normal sample preparation techniques that were commonly employed by the three different labs (each lab practiced slightly different specimen preparation techniques). The second set of samples consisted of eight specimens that had been ground and polished at a single laboratory. The companion labs were only supposed to retouch the sample surfaces if they exhibited major flaws. In general, the study indicated that the image analysis test results for entrained air content exhibited good to strong correlation to the average values determined via the linear traverse technique. Specimens ground and polished in a single laboratory and then circulated to the other participating laboratories for the air content determinations exhibited the strongest correlation between the image analysis and linear traverse techniques (coefficient of determination, r-squared = 0.96, for n=8). Specimens ground and polished at each of the individual laboratories exhibited considerably more scatter (coefficient of determination, r-squared = 0.78, for n=16). The image analysis technique tended to produce low estimates of the specific surface of the voids when compared to the results from the linear traverse method. This caused the image analysis spacing factor calculations to produce larger values than those obtained from the linear traverse tests. The image analysis spacing factors were still successful at distinguishing between the frost-prone test specimens and the other (more durable) test specimens that were studied in this research project.
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Involuntary choreiform movements are a clinical hallmark of Huntington's disease. Studies in clinically affected patients suggest a shift of motor activations to parietal cortices in response to progressive neurodegeneration. Here, we studied pre-symptomatic gene carriers to examine the compensatory mechanisms that underlie the phenomenon of retained motor function in the presence of degenerative change. Fifteen pre-symptomatic gene carriers and 12 matched controls performed button presses paced by a metronome at either 0.5 or 2 Hz with four fingers of the right hand whilst being scanned with functional magnetic resonance imaging. Subjects pressed buttons either in the order of a previously learnt 10-item finger sequence, from left to right, or kept still. Error rates ranged from 2% to 7% in the pre-symptomatic gene carriers and from 0.5% to 4% in controls, depending on the condition. No significant difference in task performance was found between groups for any of the conditions. Activations in the supplementary motor area (SMA) and superior parietal lobe differed with gene status. Compared with healthy controls, gene carriers showed greater activations of left caudal SMA with all movement conditions. Activations correlated with increasing speed of movement were greater the closer the gene carriers were to estimated clinical diagnosis, defined by the onset of unequivocal motor signs. Activations associated with increased movement complexity (i.e. with the pre-learnt 10-item sequence) decreased in the rostral SMA with nearing diagnostic onset. The left superior parietal lobe showed reduced activation with increased movement complexity in gene carriers compared with controls, and in the right superior parietal lobe showed greater activations with all but the most demanding movements. We identified a complex pattern of motor compensation in pre-symptomatic gene carriers. The results show that preclinical compensation goes beyond a simple shift of activity from premotor to parietal regions involving multiple compensatory mechanisms in executive and cognitive motor areas. Critically, the pattern of motor compensation is flexible depending on the actual task demands on motor control.