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Статті в журналах з теми "Traitement des données multimodales":
Cartaud, Alice, and Yann Coello. "The Sensorimotor Foundations of Interpersonal Space Regulation." Intellectica. Revue de l'Association pour la Recherche Cognitive 74, no. 1 (2021): 79–100. http://dx.doi.org/10.3406/intel.2021.1986.
Bourcier, Simon, Maxime Coutrot, and Matthieu Schmidt. "Crise aiguë thyrotoxique en réanimation." Médecine Intensive Réanimation 33, no. 2 (June 7, 2024): 141–52. http://dx.doi.org/10.37051/mir-00233.
Ait, Yala Camila. "Les contingences liées au recueil de données multimodales en entreprise." Traduction et Langues 18, no. 2 (December 31, 2019): 92–105. http://dx.doi.org/10.52919/translang.v18i2.431.
VERGES, Pierre. "Traitement des données à facettes." Sociologie et sociétés 25, no. 2 (September 30, 2002): 37–46. http://dx.doi.org/10.7202/001824ar.
Pellerin, Martine. "L’usage des technologies numériques pour le développement de compétences multimodales en littératie au 21e siècle." Éducation et francophonie 45, no. 2 (February 27, 2018): 85–106. http://dx.doi.org/10.7202/1043530ar.
Le Rutte, Mathijs. "Sécurité et traitement des données personnelles." Cultures & conflits, no. 76 (December 15, 2009): 87–100. http://dx.doi.org/10.4000/conflits.17793.
Becker, F. "Traitement actuel des Varices. Données EBM." Journal des Maladies Vasculaires 32 (March 2007): 4. http://dx.doi.org/10.1016/j.jmv.2007.01.063.
Jaccard, A. "Traitement de l'amylose AL, données actuelles." La Revue de Médecine Interne 27, no. 11 (November 2006): 809–12. http://dx.doi.org/10.1016/j.revmed.2006.06.013.
Mosio, D., C. Betrancourt, F. Lefebvre, D. Boquet, P. Pronier, and H. Verhaeghe. "Le traitement automatisé des données d’autosurveillance des systèmes d’assainissement." Techniques Sciences Méthodes, no. 5 (May 2019): 101–10. http://dx.doi.org/10.1051/tsm/201905101.
Bourquin, Céline. "Données linguistiques, données sociolinguistiques: le traitement labovien du vernaculaire africain-américain." Travaux neuchâtelois de linguistique, no. 40 (June 1, 2004): 11–26. http://dx.doi.org/10.26034/tranel.2004.2596.
Дисертації з теми "Traitement des données multimodales":
Guislain, Maximilien. "Traitement joint de nuage de points et d'images pour l'analyse et la visualisation des formes 3D." Thesis, Lyon, 2017. http://www.theses.fr/2017LYSE1219/document.
Recent years saw a rapid development of city digitization technologies. Acquisition campaigns covering entire cities are now performed using LiDAR (Light Detection And Ranging) scanners embedded aboard mobile vehicles. These acquisition campaigns yield point clouds, composed of millions of points, representing the buildings and the streets, and may also contain a set of images of the scene. The subject developed here is the improvement of the point cloud using the information contained in the camera images. This thesis introduces several contributions to this joint improvement. The position and orientation of acquired images are usually estimated using devices embedded with the LiDAR scanner, even if this information is inaccurate. To obtain the precise registration of an image on a point cloud, we propose a two-step algorithm which uses both Mutual Information and Histograms of Oriented Gradients. The proposed method yields an accurate camera pose, even when the initial estimations are far from the real position and orientation. Once the images have been correctly registered, it is possible to use them to color each point of the cloud while using the variability of the point of view. This is done by minimizing an energy considering the different colors associated with a point and the potential colors of its neighbors. Illumination changes can also change the color assigned to a point. Notably, this color can be affected by cast shadows. These cast shadows are changing with the sun position, it is therefore necessary to detect and correct them. We propose a new method that analyzes the joint variation of the reflectance value obtained by the LiDAR and the color of the points. By detecting enough interfaces between shadow and light, we can characterize the luminance of the scene and to remove the cast shadows. The last point developed in this thesis is the densification of a point cloud. Indeed, the local density of a point cloud varies and is sometimes insufficient in certain areas. We propose a directly applicable approach to increase the density of a point cloud using multiple images
Cavalcante, Aguilar Paulo Armando. "Réseaux Évidentiels pour la fusion de données multimodales hétérogènes : application à la détection de chutes." Phd thesis, Institut National des Télécommunications, 2012. http://tel.archives-ouvertes.fr/tel-00789773.
Chlaily, Saloua. "Modèle d'interaction et performances du traitement du signal multimodal." Thesis, Université Grenoble Alpes (ComUE), 2018. http://www.theses.fr/2018GREAT026/document.
The joint processing of multimodal measurements is supposed to lead to better performances than those obtained using a single modality or several modalities independently. However, in literature, there are examples that show that is not always true. In this thesis, we analyze, in terms of mutual information and estimation error, the different situations of multimodal analysis in order to determine the conditions to achieve the optimal performances.In the first part, we consider the simple case of two or three modalities, each associated with noisy measurement of a signal. These modalities are linked through the correlations between the useful parts of the signal and the correlations between the noises. We show that the performances are improved if the links between the modalities are exploited. In the second part, we study the impact on performance of wrong links between modalities. We show that these false assumptions decline the performance, which can become lower than the performance achieved using a single modality.In the general case, we model the multiple modalities as a noisy Gaussian channel. We then extend literature results by considering the impact of the errors on signal and noise probability densities on the information transmitted by the channel. We then analyze this relationship in the case of a simple model of two modalities. Our results show in particular the unexpected fact that a double mismatch of the noise and the signal can sometimes compensate for each other, and thus lead to very good performances
Aron, Michaël. "Acquisition et modélisation de données articulatoires dans un contexte multimodal." Thesis, Nancy 1, 2009. http://www.theses.fr/2009NAN10097/document.
There is no single technique that will allow all relevant behaviour of the speech articulators (lips, tongue, palate...) to be spatially ant temporally acquired. Thus, this thesis investigates the fusion of multimodal articulatory data. A framework is described in order to acquire and fuse automatically an important database of articulatory data. This includes: 2D Ultrasound (US) data to recover the dynamic of the tongue, stereovision data to recover the 3D dynamic of the lips, electromagnetic sensors that provide 3D position of points on the face and the tongue, and 3D Magnetic Resonance Imaging (MRI) that depict the vocal tract for various sustained articulations. We investigate the problems of the temporal synchronization and the spatial registration between all these modalities, and also the extraction of the shape articulators from the data (tongue tracking in US images). We evaluate the uncertainty of our system by quantifying the spatial and temporal inaccuracies of the components of the system, both individually and in combination. Finally, the fused data are evaluated on an existing articulatory model to assess their quality for an application in speech production
Chesnel, Anne-Lise. "Quantification de dégâts sur le bâti liés aux catastrophes majeures par images satellite multimodales très haute résolution." Phd thesis, École Nationale Supérieure des Mines de Paris, 2008. http://pastel.archives-ouvertes.fr/pastel-00004211.
Boscaro, Anthony. "Analyse multimodale et multicritères pour l'expertise et la localisation de défauts dans les composants électriques modernes." Thesis, Bourgogne Franche-Comté, 2017. http://www.theses.fr/2017UBFCK014/document.
The purpose of this manuscript is to exhibit the research work solving the issue of data processing stem from defect localization techniques. This step being decisive in the failure analysis process, scientists have to harness data coming from light emission and laser techniques. Nevertheless, this analysis process is sequential and only depends on the expert’s decision. This factor leads to a not quantified probability of localization. Consequently to solve these issues, a multimodaland multicriteria analysis has been developped, taking advantage of the heterogeneous and complementary nature of light emission and laser probing techniques. This kind of process is based on advanced level tools such as signal/image processing and data fusion. The final aim being to provide a quantitive and qualitative decision help for the experts.The first part of this manuscript is dedicated to the description of the entire process for 1D and 2D data enhancement. Thereafter, the spatio-temporal analysis of laser probing waveforms will be tackled. Finally, the last part highlights the decision support brought by data fusion
Wang, Xin. "Gaze based weakly supervised localization for image classification : application to visual recognition in a food dataset." Electronic Thesis or Diss., Paris 6, 2017. http://www.theses.fr/2017PA066577.
In this dissertation, we discuss how to use the human gaze data to improve the performance of the weak supervised learning model in image classification. The background of this topic is in the era of rapidly growing information technology. As a consequence, the data to analyze is also growing dramatically. Since the amount of data that can be annotated by the human cannot keep up with the amount of data itself, current well-developed supervised learning approaches may confront bottlenecks in the future. In this context, the use of weak annotations for high-performance learning methods is worthy of study. Specifically, we try to solve the problem from two aspects: One is to propose a more time-saving annotation, human eye-tracking gaze, as an alternative annotation with respect to the traditional time-consuming annotation, e.g. bounding box. The other is to integrate gaze annotation into a weakly supervised learning scheme for image classification. This scheme benefits from the gaze annotation for inferring the regions containing the target object. A useful property of our model is that it only exploits gaze for training, while the test phase is gaze free. This property further reduces the demand of annotations. The two isolated aspects are connected together in our models, which further achieve competitive experimental results
Wang, Xin. "Gaze based weakly supervised localization for image classification : application to visual recognition in a food dataset." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066577/document.
In this dissertation, we discuss how to use the human gaze data to improve the performance of the weak supervised learning model in image classification. The background of this topic is in the era of rapidly growing information technology. As a consequence, the data to analyze is also growing dramatically. Since the amount of data that can be annotated by the human cannot keep up with the amount of data itself, current well-developed supervised learning approaches may confront bottlenecks in the future. In this context, the use of weak annotations for high-performance learning methods is worthy of study. Specifically, we try to solve the problem from two aspects: One is to propose a more time-saving annotation, human eye-tracking gaze, as an alternative annotation with respect to the traditional time-consuming annotation, e.g. bounding box. The other is to integrate gaze annotation into a weakly supervised learning scheme for image classification. This scheme benefits from the gaze annotation for inferring the regions containing the target object. A useful property of our model is that it only exploits gaze for training, while the test phase is gaze free. This property further reduces the demand of annotations. The two isolated aspects are connected together in our models, which further achieve competitive experimental results
Chen, Jianan. "Deep Learning Based Multimodal Retrieval." Electronic Thesis or Diss., Rennes, INSA, 2023. http://www.theses.fr/2023ISAR0019.
Multimodal tasks play a crucial role in the progression towards achieving general artificial intelligence (AI). The primary goal of multimodal retrieval is to employ machine learning algorithms to extract relevant semantic information, bridging the gap between different modalities such as visual images, linguistic text, and other data sources. It is worth noting that the information entropy associated with heterogeneous data for the same high-level semantics varies significantly, posing a significant challenge for multimodal models. Deep learning-based multimodal network models provide an effective solution to tackle the difficulties arising from substantial differences in information entropy. These models exhibit impressive accuracy and stability in large-scale cross-modal information matching tasks, such as image-text retrieval. Furthermore, they demonstrate strong transfer learning capabilities, enabling a well-trained model from one multimodal task to be fine-tuned and applied to a new multimodal task, even in scenarios involving few-shot or zero-shot learning. In our research, we develop a novel generative multimodal multi-view database specifically designed for the multimodal referential segmentation task. Additionally, we establish a state-of-the-art (SOTA) benchmark and multi-view metric for referring expression segmentation models in the multimodal domain. The results of our comparative experiments are presented visually, providing clear and comprehensive insights
Guillaumin, Matthieu. "Données multimodales pour l'analyse d'image." Phd thesis, Grenoble, 2010. http://www.theses.fr/2010GRENM048.
This dissertation delves into the use of textual metadata for image understanding. We seek to exploit this additional textual information as weak supervision to improve the learning of recognition models. There is a recent and growing interest for methods that exploit such data because they can potentially alleviate the need for manual annotation, which is a costly and time-consuming process. We focus on two types of visual data with associated textual information. First, we exploit news images that come with descriptive captions to address several face related tasks, including face verification, which is the task of deciding whether two images depict the same individual, and face naming, the problem of associating faces in a data set to their correct names. Second, we consider data consisting of images with user tags. We explore models for automatically predicting tags for new images, i. E. Image auto-annotation, which can also used for keyword-based image search. We also study a multimodal semi-supervised learning scenario for image categorisation. In this setting, the tags are assumed to be present in both labelled and unlabelled training data, while they are absent from the test data. Our work builds on the observation that most of these tasks can be solved if perfectly adequate similarity measures are used. We therefore introduce novel approaches that involve metric learning, nearest neighbour models and graph-based methods to learn, from the visual and textual data, task-specific similarities. For faces, our similarities focus on the identities of the individuals while, for images, they address more general semantic visual concepts. Experimentally, our approaches achieve state-of-the-art results on several standard and challenging data sets. On both types of data, we clearly show that learning using additional textual information improves the performance of visual recognition systems
Книги з теми "Traitement des données multimodales":
Dvorchik, Sheila. Les applications du traitement des données. Montréal: Lidec, 1993.
Abdi, Hervé. Introduction au traitement statistique des données expérimentales. Grenoble: Presses Universitaires de Grenoble, 1987.
Mattatia, Fabrice. Traitement des données personnelles: Le guide juridique. Paris: Eyrolles, 2013.
Brien, Robert. Comptabilité 2: Analyse et traitement des données du cycle comptable. 5th ed. Montréal: Gaëtan Morin, 2005.
Dufournaud, Jean-Luc. Informatique et libertés: Les banques et le traitement des données. Paris: AFB diffusion, 1997.
Brien, Robert. Comptabilité 3: Analyse et traitement des données en comptabilité spécialisée. Montréal: G. Morin, 2005.
Cottet, Francis. Traitement des signaux et acquisition de données: Cours et exercices corrigés. 3rd ed. Paris: Dunod, 2009.
Boyer, Diane. Les mathématiques...un peu, beaucoup, à la folie!: Traitement des données et probabilité. Ottawa, Ont: CFORP, 2004.
Boyer, Diane. Les mathématiques...un peu, beaucoup, à la folie!: Traitement des données et probabilité. Ottawa, Ont: CFORP, 2004.
Morin-Labatut, Gisèle. Manuel de traitement des données bibliographiques dans les systèmes d'information relatifs au développement. Ottawa, Ont: Centre de recherches pour le développement international, 1988.
Частини книг з теми "Traitement des données multimodales":
DAUL, Christian, and Walter BLONDEL. "Imagerie endoscopique multimodale et multispectrale à champ de vue étendu." In Imageries optiques non conventionnelles pour la biologie, 207–45. ISTE Group, 2023. http://dx.doi.org/10.51926/iste.9132.ch7.
Colón de Carvajal, Isabel. "Chapitre 8. Traitement multimodal des données versus analyse multimodale des interactions : perspective de l’ethnométhodologie et de l’analyse conversationnelle." In Multimodalité du langage dans les interactions et l’acquisition, 211–51. UGA Éditions, 2019. http://dx.doi.org/10.4000/books.ugaeditions.10992.
"LE TRAITEMENT DES DONNÉES." In L'étude de cas comme méthode de recherche, 2e édition, 69–82. Presses de l'Université du Québec, 2011. http://dx.doi.org/10.2307/j.ctv18ph7wf.10.
"LE TRAITEMENT DES DONNÉES:." In L'analyse de contenu, 123–52. Presses de l'Université du Québec, 2011. http://dx.doi.org/10.2307/j.ctv18pgv49.14.
"Le traitement des données ontariennes." In Récoltes des forêts publiques au Québec et en Ontario, 1840-1900, 149–51. McGill-Queen's University Press, 1999. http://dx.doi.org/10.1515/9780773567429-016.
"Traitement, analyse et diffusion des données." In Lignes directrices pour la production de statistiques sur la propriété d’actifs tenant compte du genre, 163–211. United Nations, 2021. http://dx.doi.org/10.18356/9789213632512c008.
Aujoulat, Norbert. "Chapitre 3. Le traitement des données." In Le relevé des oeuvres pariétales paléolithiques, 85–105. Éditions de la Maison des sciences de l’homme, 1987. http://dx.doi.org/10.4000/books.editionsmsh.32975.
ABDELHEDI, Manel, and Omessaad HAMDI. "Sécurité du traitement des données médicales." In Gestion de la sécurité en e-santé, 183–211. ISTE Group, 2024. http://dx.doi.org/10.51926/iste.9179.ch8.
"Annexe 4 : Le traitement des données climatiques." In Une introduction à la dynamique des océans et du climat, 577–98. EDP Sciences, 2020. http://dx.doi.org/10.1051/978-2-7598-2390-1-015.
"Annexe 4 : Le traitement des données climatiques." In Une introduction à la dynamique des océans et du climat, 577–98. EDP Sciences, 2020. http://dx.doi.org/10.1051/978-2-7598-2390-1.c015.
Тези доповідей конференцій з теми "Traitement des données multimodales":
Coste–Delclaux, Mireille, Cédric Jouanne, and Claude Mounier. "Galilée : Outil de traitement des données nucléaires." In Données nucléaires : avancées et défis à relever. Les Ulis, France: EDP Sciences, 2014. http://dx.doi.org/10.1051/jtsfen/2014don09.
Romanet, I., J. H. Catherine, P. Laurent, R. Lan, and E. Dubois. "Efficacité de l’ostéotomie interalvéolaire par piezocision : revue de la littérature." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603010.
Fricain, J. C. "Mucites : une prise en charge basée sur la preuve." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206601008.
Parisot, Jean-Paul, Sylvain Capo, Stéphane Bujan, Nadia Senechal, and Jean Brillet. "Traitement des données topographiques et bathymétriques acquises sur le littoral aquitain : optimisation des mesures effectuées en quad et au théodolite." In Journées Nationales Génie Côtier - Génie Civil. Editions Paralia, 2008. http://dx.doi.org/10.5150/jngcgc.2008.057-p.
Gonzalez, JM, JP Le Mouel, P. Basile, V. Vitton, and M. Barthet. "Mucosectomie anti-reflux (ARMS) dans le traitement du reflux gastro-oesophagien réfractaire aux IPP: Etude pilote évaluant la faisabilité et données préliminaires d'éfficacité." In Journées Francophones d'Hépato-Gastroentérologie et d'Oncologie Digestive (JFHOD). Georg Thieme Verlag KG, 2019. http://dx.doi.org/10.1055/s-0039-1680889.
Benzina, Ouafae. "Du lexique de l'eau dans Mont-Oriol et Pierre et Jean de Guy de Maupassant." In XXV Coloquio AFUE. Palabras e imaginarios del agua. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/xxvcoloquioafue.2016.3081.
Dubuc, A., P. Monsarrat, S. Laurencin-Dalicieux, F. Virard, J. P. Sarrette, N. Merbahi, and S. Cousty. "Application du plasma atmosphérique froid en oncologie : une revue systématique." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603018.
ORLIANGES, Jean-Christophe, Younes El Moustakime, Aurelian Crunteanu STANESCU, Ricardo Carrizales Juarez, and Oihan Allegret. "Retour vers le perceptron - fabrication d’un neurone synthétique à base de composants électroniques analogiques simples." In Les journées de l'interdisciplinarité 2023. Limoges: Université de Limoges, 2024. http://dx.doi.org/10.25965/lji.761.
Ordioni, U., G. Labrosse, F. Campana, R. Lan, J. H. Catherine, and A. F. Albertini. "Granulomatose oro-faciale révélatrice d’une maladie de Crohn : présentation d’un cas." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603017.
Hadj SaÏd, M., L. Thollon, Y. Godio-Raboutet, J. H. Catherine, C. M. Chossegros, and D. Tardivo. "Modélisation 3D de l’os maxillaire dans l’analyse par éléments finis en implantologie orale : une nouvelle approche utilisant CBCT et anthropométrie." In 66ème Congrès de la SFCO. Les Ulis, France: EDP Sciences, 2020. http://dx.doi.org/10.1051/sfco/20206603022.
Звіти організацій з теми "Traitement des données multimodales":
Dudoit, Alain. Les espaces européens communs de données : une initiative structurante nécessaire et adaptable au Canada. CIRANO, October 2023. http://dx.doi.org/10.54932/ryht5065.
Dudley, J. P., and S. V. Samsonov. Système de traitement automatisé du gouvernement canadien pour la détection des variations et l'analyse des déformations du sol à partir des données de radar à synthèse d'ouverture de RADARSAT-2 et de la mission de la Constellation RADARSAT : description et guide de l'utilisateur. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/329134.