Готові списки джерел за темами / Images assimilation

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Добірка наукової літератури з теми "Images assimilation"

Автор: Grafiati
Опубліковано: 21 липня 2022
Оновлено: 8 серпня 2022

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Статті в журналах з теми "Images assimilation"

1

Plu, M. "A variational formulation for translation and assimilation of coherent structures." Nonlinear Processes in Geophysics 20, no. 5 (October 17, 2013): 793–801. http://dx.doi.org/10.5194/npg-20-793-2013.

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Анотація:
Abstract. The assimilation of observations from teledetected images in geophysical models requires one to develop algorithms that would account for the existence of coherent structures. In the context of variational data assimilation, a method is proposed to allow the background to be translated so as to fit structure positions deduced from images. Translation occurs as a first step before assimilating all the observations using a classical assimilation procedure with specific covariances for the translated background. A simple validation is proposed using a dynamical system based on the one-dimensional complex Ginzburg–Landau equation in a regime prone to phase and amplitude errors. Assimilation of observations after background translation leads to better scores and a better representation of extremas than the method without translation.
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2

Le Dimet, F. X., I. Souopgui, O. Titaud, V. Shutyaev, and M. Y. Hussaini. "Toward the assimilation of images." Nonlinear Processes in Geophysics 22, no. 1 (January 13, 2015): 15–32. http://dx.doi.org/10.5194/npg-22-15-2015.

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Анотація:
Abstract. The equations that govern geophysical fluids (namely atmosphere, ocean and rivers) are well known but their use for prediction requires the knowledge of the initial condition. In many practical cases, this initial condition is poorly known and the use of an imprecise initial guess is not sufficient to perform accurate forecasts because of the high sensitivity of these systems to small perturbations. As every situation is unique, the only additional information that can help to retrieve the initial condition are observations and statistics. The set of methods that combine these sources of heterogeneous information to construct such an initial condition are referred to as data assimilation. More and more images and sequences of images, of increasing resolution, are produced for scientific or technical studies. This is particularly true in the case of geophysical fluids that are permanently observed by remote sensors. However, the structured information contained in images or image sequences is not assimilated as regular observations: images are still (under-)utilized to produce qualitative analysis by experts. This paper deals with the quantitative assimilation of information provided in an image form into a numerical model of a dynamical system. We describe several possibilities for such assimilation and identify associated difficulties. Results from our ongoing research are used to illustrate the methods. The assimilation of image is a very general framework that can be transposed in several scientific domains.
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3

Le Dimet, F. X., I. Souopgui, O. Titaud, and V. Shutyaev. "Toward the assimilation of images." Nonlinear Processes in Geophysics Discussions 1, no. 2 (August 19, 2014): 1381–430. http://dx.doi.org/10.5194/npgd-1-1381-2014.

Повний текст джерела
Анотація:
Abstract. The equations that govern geophysical fluids (namely atmosphere, ocean and rivers) are well known but their use for prediction requires the knowledge of the initial condition. In many practical cases, this initial condition is poorly known and the use of an imprecise initial guess is not sufficient to perform accurate forecasts because of the high sensitivity of these systems to small perturbations. As every situation is unique, the only additional information than can help to retrieve the initial condition are observations and statistics. The set of methods that combine these sources of heterogeneous information to construct such an initial condition are referred to as data assimilation. More and more images and sequences of images, of increasing resolution, are produced for scientific or technical studies. This is particularly true in the case of geophysical fluids that are permanently observed by remote sensors. However, the structured information contained in images or image sequences is not assimilated as regular observations: images are still (under)utilized to produce qualitative analysis by experts. This paper deals with the quantitative assimilation of information provided in an image form into a numerical model of a dynamical system. We describe several possibilities for such assimilation and identify associated difficulties. Results from our ongoing research are used to illustrate the methods. The assimilation of image is a very general framework that can be transposed in several scientific domains.
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4

Li, Ya. "FEMININE ASSIMILATIONS IN TEXT FORMATION OF "THE KUKOTSKY ENIGMA" BY L. ULITSKAYA." Bulletin of Kemerovo State University, no. 2 (August 3, 2018): 199–205. http://dx.doi.org/10.21603/2078-8975-2018-2-199-205.

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Анотація:
The article features comparisons by similarity and functionally equivalent metaphors targeting the heroines of The Kukotsky Enigma by L. Ulitskaya. The author proposes to take into account the differences between logical and figurative comparisons, emphasizing its subjective character and surreal modality. Also, the author suggests that figurative and logical comparisons can be combined in a compound sentence with a comparative subordinate clause. The thematic variety of feminine images of assimilation in the novel correlates with the application of nature-related and anthroponymic comparisons. Zoomorphous type prevails in nature-related comparisons, some of them shaping the associative microfields of the main characters. An attempt is made to explain the writer's conceptual thematic purpose connected with these microfields. The textual connections between comparison and metaphor are considered to be genetically close linguistic phenomena, which are combined by the common concept of "comparative". This makes it possible 1) to maintain the perceptive integrity of thematic associative microfields with comparative dominants involved in the female images; 2) to trace the correlation of tropes with realia in textual formation. A gender approach to the description of assimilative images and the representation of a wide variety of their modes of expression in L. Ulitskaya's novel have allowed the author to reveal the idiostyle features of the female author. It includes frequent forms of assimilation accompanied by explanations and clarifications that reflect, directly or indirectly, the author's attitude (sympathy, irony, or sarcasm) towards her female characters, as well as her conceptual thematic purpose related to the main characters’ fates and that of the family of the famous gynecologist doctor Kukotsky. The article features speech differentiation in the feminine images of assimilation by the author and her characters. The analysis performed has revealed a tendency to female comparative characteristics in L. Ulitskaya’s style.
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5

Margolis, Eric, and Jeremy Rowe. "Images of assimilation: photographs of Indian schools in Arizona." History of Education 33, no. 2 (March 2004): 199–230. http://dx.doi.org/10.1080/0046760032000151456.

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6

Chen, Pengfei. "Estimation of Winter Wheat Grain Protein Content Based on Multisource Data Assimilation." Remote Sensing 12, no. 19 (September 30, 2020): 3201. http://dx.doi.org/10.3390/rs12193201.

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Анотація:
Data assimilation is a robust method to predict crop biophysical and biochemical parameters. However, no previous study has attempted to predict grain protein content (GPC) at a regional scale using this method. This study explored the feasibility of designing an assimilation model for wheat GPC estimation using remote sensing, a crop growth model, and a priori knowledge. The data included a field experiment and regional sampling data, and Landsat Operational Land Imager images were employed, with the CERES (Crop Environment REsource Synthesis)-Wheat model used as simulation model. To select an optimal method for data assimilation in GPC prediction, different state variable scenarios and cost function solving algorithm scenarios were compared. Additionally, to determine whether a priori information could improve GPC prediction, the collected leaf area index (LAI) and leaf N content sampling data and the range of GPC in the study region were used to constrain the data assimilation process. Furthermore, the data assimilation method was compared to the use of only the CERES-Wheat model. The results showed that GPC could be predicted by remote sensing observation, a crop growth model, and a priori knowledge at regional scale, where the use of data assimilation improved the GPC prediction compared to using only the CERES-Wheat model.
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7

Cenci, Luca, Luca Pulvirenti, Giorgio Boni, and Nazzareno Pierdicca. "Defining a Trade-off Between Spatial and Temporal Resolution of a Geosynchronous SAR Mission for Soil Moisture Monitoring." Remote Sensing 10, no. 12 (December 4, 2018): 1950. http://dx.doi.org/10.3390/rs10121950.

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Анотація:
The next generation of synthetic aperture radar (SAR) systems could foresee satellite missions based on a geosynchronous orbit (GEO SAR). These systems are able to provide radar images with an unprecedented combination of spatial (≤1 km) and temporal (≤12 h) resolutions. This paper investigates the GEO SAR potentialities for soil moisture (SM) mapping finalized to hydrological applications, and defines the best compromise, in terms of image spatio-temporal resolution, for SM monitoring. A synthetic soil moisture–data assimilation (SM-DA) experiment was thus set up to evaluate the impact of the hydrological assimilation of different GEO SAR-like SM products, characterized by diverse spatio-temporal resolutions. The experiment was also designed to understand if GEO SAR-like SM maps could provide an added value with respect to SM products retrieved from SAR images acquired from satellites flying on a quasi-polar orbit, like Sentinel-1 (POLAR SAR). Findings showed that GEO SAR systems provide a valuable contribution for hydrological applications, especially if the possibility to generate many sub-daily observations is sacrificed in favor of higher spatial resolution. In the experiment, it was found that the assimilation of two GEO SAR-like observations a day, with a spatial resolution of 100 m, maximized the performances of the hydrological predictions, for both streamflow and SM state forecasts. Such improvements of the model performances were found to be 45% higher than the ones obtained by assimilating POLAR SAR-like SM maps.
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8

Michel, Yann. "Data Assimilation of Tropopause Height Using Dry Intrusion Observations." Monthly Weather Review 138, no. 1 (January 1, 2010): 101–22. http://dx.doi.org/10.1175/2009mwr2912.1.

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Анотація:
Abstract This article investigates the problem of initializing upper-level potential vorticity by using the detection of dry intrusions that can be seen in water vapor images. First, a satellite image processing technique has been developed for the identification and tracking of dry intrusions on geostationary satellite images. This technique can also be applied to images derived from model fields through a radiative transfer model. A linking algorithm automatically compares the trajectories of the dry intrusions in the model and in the satellite images. Differences of brightness temperatures are then converted to differences of tropopause height through a simple linear model, which is based on the correlation found in the background. As the scheme is likely to provide observations of the tropopause height, it also suggests that a space-alignment representation of the errors be used. A simple one-dimensional study provides a depiction of the background error covariance in alignment space, which is compared to the traditional approach of background error covariance in amplitude space. An approximate form of the Ertel potential vorticity operator is then used to incorporate pseudo-observations inside a global four-dimensional variational assimilation scheme. A case study of cyclogenesis highlights the difference between the amplitude–space assimilation of potential vorticity values and the alignment space assimilation of the height of the tropopause.
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9

Liu, Zhengchun, Zhanjun Xu, Rutian Bi, Chao Wang, Peng He, Yaodong Jing, and Wude Yang. "Estimation of Winter Wheat Yield in Arid and Semiarid Regions Based on Assimilated Multi-Source Sentinel Data and the CERES-Wheat Model." Sensors 21, no. 4 (February 10, 2021): 1247. http://dx.doi.org/10.3390/s21041247.

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Анотація:
The farmland area in arid and semiarid regions accounts for about 40% of the total area of farmland in the world, and it continues to increase. It is critical for global food security to predict the crop yield in arid and semiarid regions. To improve the prediction of crop yields in arid and semiarid regions, we explored data assimilation-crop modeling strategies for estimating the yield of winter wheat under different water stress conditions across different growing areas. We incorporated leaf area index (LAI) and soil moisture derived from multi-source Sentinel data with the CERES-Wheat model using ensemble Kalman filter data assimilation. According to different water stress conditions, different data assimilation strategies were applied to estimate winter wheat yields in arid and semiarid areas. Sentinel data provided LAI and soil moisture data with higher frequency (<14 d) and higher precision, with root mean square errors (RMSE) of 0.9955 m2 m−2 and 0.0305 cm3 cm−3, respectively, for data assimilation-crop modeling. The temporal continuity of the CERES-Wheat model and the spatial continuity of the remote sensing images obtained from the Sentinel data were integrated using the assimilation method. The RMSE of LAI and soil water obtained by the assimilation method were lower than those simulated by the CERES-Wheat model, which were reduced by 0.4458 m2 m−2 and 0.0244 cm3 cm−3, respectively. Assimilation of LAI independently estimated yield with high precision and efficiency in irrigated areas for winter wheat, with RMSE and absolute relative error (ARE) of 427.57 kg ha−1 and 6.07%, respectively. However, in rain-fed areas of winter wheat under water stress, assimilating both LAI and soil moisture achieved the highest accuracy in estimating yield (RMSE = 424.75 kg ha−1, ARE = 9.55%) by modifying the growth and development of the canopy simultaneously and by promoting soil water balance. Sentinel data can provide high temporal and spatial resolution data for deriving LAI and soil moisture in the study area, thereby improving the estimation accuracy of the assimilation model at a regional scale. In the arid and semiarid region of the southeastern Loess Plateau, assimilation of LAI independently can obtain high-precision yield estimation of winter wheat in irrigated area, while it requires assimilating both LAI and soil moisture to achieve high-precision yield estimation in the rain-fed area.
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10

Zhuo, Wen, Jianxi Huang, Li Li, Xiaodong Zhang, Hongyuan Ma, Xinran Gao, Hai Huang, Baodong Xu, and Xiangming Xiao. "Assimilating Soil Moisture Retrieved from Sentinel-1 and Sentinel-2 Data into WOFOST Model to Improve Winter Wheat Yield Estimation." Remote Sensing 11, no. 13 (July 8, 2019): 1618. http://dx.doi.org/10.3390/rs11131618.

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Анотація:
Crop yield estimation at a regional scale over a long period of time is of great significance to food security. In past decades, the integration of remote sensing observations and crop growth models has been recognized as a promising approach for crop growth monitoring and yield estimation. Optical remote sensing data are susceptible to cloud and rain, while synthetic aperture radar (SAR) can penetrate through clouds and has all-weather capabilities. This allows for more reliable and consistent crop monitoring and yield estimation in terms of radar sensor data. The aim of this study is to improve the accuracy for winter wheat yield estimation by assimilating time series soil moisture images, which are retrieved by a water cloud model using SAR and optical data as input, into the crop model. In this study, SAR images were acquired by C-band SAR sensors boarded on Sentinel-1 satellites and optical images were obtained from a Sentinel-2 multi-spectral instrument (MSI) for Hengshui city of Hebei province in China. Remote sensing data and ground data were all collected during the main growing season of winter wheat. Both the normalized difference vegetation index (NDVI), derived from Sentinel-2, and backscattering coefficients and polarimetric indicators, computed from Sentinel-1, were used in the water cloud model to derive time series soil moisture (SM) images. To improve the prediction of crop yields at the field scale, we incorporated remotely sensed soil moisture into the World Food Studies (WOFOST) model using the Ensemble Kalman Filter (EnKF) algorithm. In general, the trend of soil moisture inversion was consistent with the ground measurements, with the coefficient of determination (R2) equal to 0.45, 0.53, and 0.49, respectively, and RMSE was 9.16%, 7.43%, and 8.53%, respectively, for three observation dates. The winter wheat yield estimation results showed that the assimilation of remotely sensed soil moisture improved the correlation of observed and simulated yields (R2 = 0.35; RMSE =934 kg/ha) compared to the situation without data assimilation (R2 = 0.21; RMSE = 1330 kg/ha). Consequently, the results of this study demonstrated the potential and usefulness of assimilating SM retrieved from both Sentinel-1 C-band SAR and Sentinel-2 MSI optical remote sensing data into WOFOST model for winter wheat yield estimation and could also provide a reference for crop yield estimation with data assimilation for other crop types.
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Більше джерел

Дисертації з теми "Images assimilation"

1

Feyeux, Nelson. "Transport optimal pour l'assimilation de données images." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAM076/document.

Повний текст джерела
Анотація:
Pour prédire l'évolution d'un système physique, nous avons besoin d'initialiser le modèle mathématique le représentant, donc d'estimer la valeur de l'état du système au temps initial. Cet état n'est généralement pas directement mesurable car souvent trop complexe. En revanche, nous disposons d'informations du système, prises à des temps différents, incomplètes, mais aussi entachées d'erreurs, telles des observations, de précédentes estimations, etc. Combiner ces différentes informations partielles et imparfaites pour estimer la valeur de l'état fait appel à des méthodes d'assimilation de données dont l'idée est de trouver un état initial proche de toutes les informations. Ces méthodes sont très utilisées en météorologie. Nous nous intéressons dans cette thèse à l'assimilation d'images, images qui sont de plus en plus utilisées en tant qu'observations. La spécificité de ces images est leur cohérence spatiale, l'oeil humain peut en effet percevoir des structures dans les images que les méthodes classiques d'assimilation ne considèrent généralement pas. Elles ne tiennent compte que des valeurs de chaque pixel, ce qui résulte dans certains cas à des problèmes d'amplitude dans l'état initial estimé. Pour résoudre ce problème, nous proposons de changer d'espace de représentation des données : nous plaçons les données dans un espace de Wasserstein où la position des différentes structures compte. Cet espace, équipé d'une distance de Wasserstein, est issue de la théorie du transport optimal et trouve beaucoup d'applications en imagerie notamment.Dans ce travail nous proposons une méthode d'assimilation variationnelle de données basée sur cette distance de Wasserstein. Nous la présentons ici, ainsi que les algorithmes numériques liés et des expériences montrant ses spécificités. Nous verrons dans les résultats comment elle permet de corriger ce qu'on appelle erreurs de position
Forecasting of a physical system is computed by the help of a mathematical model. This model needs to be initialized by the state of the system at initial time. But this state is not directly measurable and data assimilation techniques are generally used to estimate it. They combine all sources of information such as observations (that may be sparse in time and space and potentially include errors), previous forecasts, the model equations and error statistics. The main idea of data assimilation techniques is to find an initial state accounting for the different sources of informations. Such techniques are widely used in meteorology, where data and particularly images are more and more numerous due to the increasing number of satellites and other sources of measurements. This, coupled with developments of meteorological models, have led to an ever-increasing quality of the forecast.Spatial consistency is one specificity of images. For example, human eyes are able to notice structures in an image. However, classical methods of data assimilation do not handle such structures because they take only into account the values of each pixel separately. In some cases it leads to a bad initial condition. To tackle this problem, we proposed to change the representation of an image: images are considered here as elements of the Wasserstein space endowed with the Wasserstein distance coming from the optimal transport theory. In this space, what matters is the positions of the different structures.This thesis presents a data assimilation technique based on this Wasserstein distance. This technique and its numerical procedure are first described, then experiments are carried out and results shown. In particularly, it appears that this technique was able to give an analysis of corrected position
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2

Billet, Florence. "Assimilation de données images pour la personnalisation d'un modèle électromécanique du coeur." Phd thesis, Université de Nice Sophia-Antipolis, 2010. http://tel.archives-ouvertes.fr/tel-00639921.

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Анотація:
Les données cliniques disponibles pour le diagnostic et la planification de thérapies sont de plus en plus variées et complexes, ce qui apporte des informations plus riches, mais rend la tâche du médecin difficile. Les modèles informatiques de cœur peuvent intégrer et analyser ces données en s'adaptant à chaque patient de manière à proposer au médecin une vue intégrée ainsi que des paramètres intrinsèques. Cependant, il faut pour cela mettre en place des méthodes d'ajustement automatique de ces modèles mathématiques aux données du patient. Dans cette thèse, nous proposons une méthodologie pour personnaliser un modèle électromécanique à partir de séquences temporelles d'images volumiques telles que des séquences ciné-IRM ou scanner. Cette personnalisation consiste en l'estimation de l'état (position/vitesse) et des paramètres électriques et mécaniques du modèle électromécanique. Nous nous intéressons ici à l'estimation du mouvement cardiaque et des paramètres de contractilité du modèle électromécanique. Dans un premier temps, la modélisation des différentes phases cardiaques a été améliorée et une étude de sensibilité a été effectuée. Puis, les approches de segmentation et de suivi du mouvement par modèles déformables ont été généralisées en couplant un modèle déformable proactif avec des séquences d'images 3D. Cette méthode est évaluée sur des données synthétiques et appliquée à des séquences ciné-IRM ou scanner. Enfin, une méthode d'estimation automatique des paramètres de contractilité à partir de séquences d'images 3D est proposée, la principale difficulté provenant des non-linéarités liées aux changements de phases. La méthode proposée est fondée sur l'assimilation de données variationnelle et le gradient du critère d'erreur est calculé à l'aide de la méthode de l'état adjoint. Cette méthode est évaluée sur des données synthétiques avant d'être appliquée à des ciné-IRM cliniques. Cette thèse pose des bases de la personnalisation du modèle électromécanique du cœur et ouvre des perspectives pour l'optimisation des traitements selon le patient considéré.
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3

Papadakis, Nicolas. "Assimilation de données images : application au suivi de courbes et de champs de vecteurs." Phd thesis, Université Rennes 1, 2007. http://tel.archives-ouvertes.fr/tel-00655898.

Повний текст джерела
Анотація:
Cette thèse traite de l'utilisation de méthodes séquentielles et variationnelles de suivi pour des problèmes de suivi dans des séquences d'images. Ces méthodes cherchent à estimer l'état d'un système à partir d'un modèle d'évolution dynamique et d'un ensemble d'observations bruitées et généralement incomplètes de l'état. Ces techniques sont appliquées à divers problèmes de vision par ordinateur: le suivi de courbe, l'estimation de champs de mouvement fluide et le suivi couplé de courbe et de champs de vecteurs. Nous montrons comment l'assimilation de données permet de gérer des occultations totales pendant le suivi d'objets sur une séquence d'images. Nous nous intéressons enfin à l'estimation de mouvement de couches atmosphériques à partir d'images satellitaires, puis étudions l'estimation de coefficients associés à des systèmes dynamiques réduits associés à la visualisation d'écoulements expérimentaux.
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4

Souopgui, Innocent. "Assimilation d'images pour les fluides géophysiques." Grenoble, 2010. http://www.theses.fr/2010GRENM071.

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Анотація:
La compréhension et la prévision de l'évolution des fluides géophysiques sont d'une importance capitale et constituent un domaine de recherche scientifique aux enjeux conséquents. Une bonne prévision est basée sur la prise en compte de toutes les informations disponibles sur le système considéré. Ces informations incluent les modèles, les observations et les connaissances a priori. L'assimilation de données permet de les combiner de façon optimale pour déterminer les entrées du modèle. Les dernières décennies ont vu croître en densité et en qualité la couverture satellitaire produisant, entre autres, des séquences d'images montrant l'évolution dynamique de certains phénomènes géophysiques tels que les dépressions et les fronts. Ces séquences d'images sont jusqu'à présent sous-utilisées en assimilation de données. Cette thèse propose une extension de l'assimilation variationnelle de données aux observations de type séquence d'images. Après avoir présenté les images, leur utilisation actuelle et ses limites, nous introduisons les notions de niveau d'interprétation, d'espaces et d'opérateur image. Ces notions sont utilisées pour formuler l'assimilation directe de séquences d'images. Nous proposons également une nouvelle approche de régularisation par diffusion généralisée pour les problèmes inverses. Les résultats préliminaires en traitement d'images et en assimilation directe de séquence d'images montrent une méthode prometteuse qui résout la plupart des problèmes rencontrés avec les approches classiques de régularisation
Understanding and forecasting the evolution of geophysical fluids is a major scientific and societal challenge. A good forecast must take into account all available information on the studied system. These informations include models, observations and a priori knowledge. Data assimilation techniques combine all these informations in a consistent way to produce model inputs. During the last decades, many satellites were launched to increase the knowledge of earth. They produce, among others, image sequences showing the dynamical evolution of geophysical processes such as depressions and fronts. These images sequences are currently under-utilized in data assimilation. This thesis presents a consistent approach for taking into account image sequences in variational data assimilation. After a presentation of images, their current use and its limitation, we introduce the concepts of interpretation level, image space and image operator used for direct image sequences assimilation. We also propose a new approach of regularization based on generalized diffusion for ill-posed inverse problems. Preliminary results on image processing and image sequences assimilation show a promising approach that solve most of the problems encountered with classical approaches of regularization
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5

Gong, Xing. "Analyse de séries temporelles d’images à moyenne résolution spatiale : reconstruction de profils de LAI, démélangeage : application pour le suivi de la végétation sur des images MODIS." Thesis, Rennes 2, 2015. http://www.theses.fr/2015REN20021/document.

Повний текст джерела
Анотація:
Cette thèse s’intéresse à l’analyse de séries temporelles d’images satellites à moyenne résolution spatiale. L’intérêt principal de telles données est leur haute répétitivité qui autorise des analyses de l’usage des sols. Cependant, deux problèmes principaux subsistent avec de telles données. En premier lieu, en raison de la couverture nuageuse, des mauvaises conditions d’acquisition, ..., ces données sont souvent très bruitées. Deuxièmement, les pixels associés à la moyenne résolution spatiale sont souvent “mixtes” dans la mesure où leur réponse spectrale est une combinaison de la réponse de plusieurs éléments “purs”. Ces deux problèmes sont abordés dans cette thèse. Premièrement, nous proposons une technique d’assimilation de données capable de recouvrer des séries temporelles cohérentes de LAI (Leaf Area Index) à partir de séquences d’images MODIS bruitées. Pour cela, le modèle de croissance de plantes GreenLab estutilisé. En second lieu, nous proposons une technique originale de démélangeage, qui s’appuie notamment sur des noyaux “élastiques” capables de gérer les spécificités des séries temporelles (séries de taille différentes, décalées dans le temps, ...)Les résultats expérimentaux, sur des données synthétiques et réelles, montrent de bonnes performances des méthodologies proposées
This PhD dissertation is concerned with time series analysis for medium spatial resolution (MSR) remote sensing images. The main advantage of MSR data is their high temporal rate which allows to monitor land use. However, two main problems arise with such data. First, because of cloud coverage and bad acquisition conditions, the resulting time series are often corrupted and not directly exploitable. Secondly, pixels in medium spatial resolution images are often “mixed” in the sense that the spectral response is a combination of the response of “pure” elements.These two problems are addressed in this PhD. First, we propose a data assimilation technique able to recover consistent time series of Leaf Area Index from corrupted MODIS sequences. To this end, a plant growth model, namely GreenLab, is used as a dynamical constraint. Second, we propose a new and efficient unmixing technique for time series. It is in particular based on the use of “elastic” kernels able to properly compare time series shifted in time or of various lengths.Experimental results are shown both on synthetic and real data and demonstrate the efficiency of the proposed methodologies
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Rose, Fiona. "Cultural identity in Roman Celtiberia : the evidence of the images and monuments, 300BC - AD100." Thesis, University of Oxford, 2003. http://ora.ox.ac.uk/objects/uuid:495111e9-ad8e-469a-a123-ec91209d8595.

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This thesis presents a study of changing constructions and perceptions of cultural identity over the period 300 BC to AD 100 in the region of northern central Spain known in antiquity as Celtiberia. Its primary focus is iconography, with images of male and female figures of particular interest. The iconography is used to map the continuities and discontinuities in a sense of Celtiberian identity, and considers the effect that interaction with non-Celtiberians, including Celts and Iberians but especially with Romans, had on this identity. A theoretical framework in which to study 'cultural identity' is proposed in the Prolegomena. After the Prolegomena, the thesis is divided into six chapters. Chapter One, Celtiberia in its Historical and Cultural Context, examines the development of Celtiberian culture and Celtiberian settlements over time, and the changes that occurred after the arrival of Romans. Chapter Two, Metallurgy and Metal Objects, looks at three categories of metal objects (fibulae, hospitium tesserae, and armaments) and asks whether the horseman motif, an important iconographic element in this thesis, is emblematic of a 'warrior aristocracy'. Chapter Three, Human and Animal Figures on Painted Pottery, studies the range of human figures found on Celtiberian ceramic vessels, considering the types of scenes and figures that were most popular. Chapter Four, Coins from Pre-Roman and Early Imperial Celtiberia, traces the development of numismatic images in the region. This chapter emphasises the so-called transitional coins, which represent the first time that Celtiberian cities were publicly identified with Roman authority on official media. Chapter Five, Men's Funerary Monuments, returns to critical analysis of the horseman motif, focusing on stelai with relief images of male figures on horseback. Chapter Six, Women's Funerary Monuments, examines the most popular visual language for Celtiberian women, the 'funerary banquet,' and places stelai bearing this theme in their wider social context. A concluding section discusses Celtiberian iconography as a whole. It also considers the role that language - Celtiberian and/or Latin - played alongside the images, and whether the phenomena of bilingualism and Latinisation of names bear 'cultural identity' significance.
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Chabot, Vincent. "Etude de représentations parcimonieuses des statistiques d'erreur d'observation pour différentes métriques. Application à l'assimilation de données images." Thesis, Grenoble, 2014. http://www.theses.fr/2014GRENM094/document.

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Les dernières décennies ont vu croître en quantité et en qualité les données satellites. Au fil des ans, ces observations ont pris de plus en plus d'importance en prévision numérique du temps. Ces données sont aujourd'hui cruciales afin de déterminer de manière optimale l'état du système étudié, et ce, notamment car elles fournissent des informations denses et de qualité dansdes zones peu observées par les moyens conventionnels. Cependant, le potentiel de ces séquences d'images est encore largement sous–exploitée en assimilation de données : ces dernières sont sévèrement sous–échantillonnées, et ce, en partie afin de ne pas avoir à tenir compte des corrélations d'erreurs d'observation.Dans ce manuscrit nous abordons le problème d'extraction, à partir de séquences d'images satellites, d'information sur la dynamique du système durant le processus d'assimilation variationnelle de données. Cette étude est menée dans un cadre idéalisé afin de déterminer l'impact d'un bruit d'observations et/ou d'occultations sur l'analyse effectuée.Lorsque le bruit est corrélé en espace, tenir compte des corrélations en analysant les images au niveau du pixel n'est pas chose aisée : il est nécessaire d'inverser la matrice de covariance d'erreur d'observation (qui se révèle être une matrice de grande taille) ou de faire des approximationsaisément inversibles de cette dernière. En changeant d'espace d'analyse, la prise en compte d'une partie des corrélations peut être rendue plus aisée. Dans ces travaux, nous proposons d'effectuer cette analyse dans des bases d'ondelettes ou des trames de curvelettes. En effet, un bruit corréléen espace n'impacte pas de la même manière les différents éléments composants ces familles. En travaillant dans ces espaces, il est alors plus aisé de tenir compte d'une partie des corrélations présentes au sein du champ d'erreur. La pertinence de l'approche proposée est présentée sur différents cas tests.Lorsque les données sont partiellement occultées, il est cependant nécessaire de savoir comment adapter la représentation des corrélations. Ceci n'est pas chose aisée : travailler avec un espace d'observation changeant au cours du temps rend difficile l'utilisation d'approximations aisément inversibles de la matrice de covariance d'erreur d'observation. Dans ces travaux uneméthode permettant d'adapter, à moindre coût, la représentations des corrélations (dans des bases d'ondelettes) aux données présentes dans chaque image est proposée. L'intérêt de cette approche est présenté dans un cas idéalisé
Recent decades have seen an increase in quantity and quality of satellite observations . Over the years , those observations has become increasingly important in numerical weather forecasting. Nowadays, these datas are crucial in order to determine optimally the state of the studied system. In particular, satellites can provide dense observations in areas poorly observed by conventionnal networks. However, the potential of such observations is clearly under--used in data assimilation : in order to avoid the management of observation errors, thinning methods are employed in association to variance inflation.In this thesis, we adress the problem of extracting information on the system dynamic from satellites images data during the variationnal assimilation process. This study is carried out in an academic context in order to quantify the influence of observation noise and of clouds on the performed analysis.When the noise is spatially correlated, it is hard to take into account such correlations by working in the pixel space. Indeed, it is necessary to invert the observation error covariance matrix (which turns out to be very huge) or make an approximation easily invertible of such a matrix. Analysing the information in an other space can make the job easier. In this manuscript, we propose to perform the analysis step in a wavelet basis or a curvelet frame. Indeed, in those structured spaces, a correlated noise does not affect in the same way the differents structures. It is then easier to take into account part of errors correlations : a suitable approximation of the covariance matrix is made by considering only how each kind of element is affected by a correlated noise. The benefit of this approach is demonstrated on different academic tests cases.However, when some data are missing one has to address the problem of adapting the way correlations are taken into account. This work is not an easy one : working in a different observation space for each image makes the use of easily invertible approximate covariance matrix very tricky. In this work a way to adapt the diagonal hypothesis of the covariance matrix in a wavelet basis, in order to take into account that images are partially hidden, is proposed. The interest of such an approach is presented in an idealised case
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Imperiale, Alexandre. "Méthodes d'assimilation de la donnée image pour la personnalisation de modèles mécaniques - Application à la mécanique cardiaque et aux images de marquage tissulaire." Phd thesis, Université Pierre et Marie Curie - Paris VI, 2013. http://tel.archives-ouvertes.fr/tel-00936027.

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Cette thèse est dédiée à l'intégration de données complexes issues de l'imagerie dans une stratégie d'assimilation de données pour des modèles mécaniques. Notre stratégie s'appuie sur des travaux récents proposant une méthode séquentielle d'assimilation de données qui se décompose en un filtre de Luenberger pour l'espace d'état et un filtre optimal réduit à l'espace des paramètres. Nous l'appliquons à l'identification de paramètres pour un modèle biomécanique du cœur et, dans ce cadre, nous formalisons la construction de comparateurs de formes évolués pour deux types de données : d'une part des données extraites d'un traitement de l'Imagerie par Résonance Magnétique (IRM) de marquage tissulaire et, d'autre part, des données plus classiques de type contours de l'objet. D'abord fondés sur des simples distances nous enrichissons ces comparateurs grâce au formalisme des courants permettant d'inscrire le contour de l'objet dans le dual d'un espace de fonctions-test appropriées. Pour chacun des comparateurs nous analysons son impact sur l'observabilité du système et, pour le cas de l'imagerie de marquage tissulaire, nous prouvons qu'ils sont équivalents à une mesure directe du déplacement. D'un point de vue numérique, la prise en compte de ces mesures complexes présente d'importantes difficultées nous poussant à mettre en place des schémas numériques originaux permettant une manipulation plus flexible des différents opérateurs d'observation. Nous profitons de ces nouveaux moyens d'extraction de l'information contenue dans les données d'imagerie pour permettre, dans des cas réalistes, l'identification de la position et de l'intensité d'un infarctus du myocarde.
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Corpetti, Thomas. "Images & télédétection : analyse de séquences à basse et très haute résolution spatiale." Habilitation à diriger des recherches, Université Rennes 1, 2011. http://tel.archives-ouvertes.fr/tel-00616558.

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Ce document d'habilitation est consacré à l'étude de séries temporelles d'images de télédétection à basse (LSR) et à très haute résolution spatiale (VHSR). Les phénomènes étudiés concernent la météorologie et l'océanographie (données LSR) et l'agriculture et le milieu urbain (données VHSR). La fréquence d'acquisition des données satellites est inversement proportionnelle à la résolution spatiale. Ainsi, pour des données LSR, la cadence d'acquisition est élevée (une images pour $15min$ avec le satellite MSG --Météosat Seconde Génération) et cela autorise l'étude des mouvement atmosphériques turbulents observés à travers le mouvement des nuages, la circulation océanique, ... Les problèmes d'analyse d'images associés concernent l'estimation du mouvement, le suivi de courbe ou encore l'interpolation de données manquantes. En ce qui concerne les données VHSR, la période séparant deux images peut varier de quelques semaines à quelques mois. Les études associées sont alors dédiées à la détection de changements structurels entre deux images. Du point de vue méthodologique, l'analyse de données LSR est principalement réalisée en introduisant des connaissances physiques a priori dans les outils classiques d'analyse d'images. Une part importante est dédiée à l'utilisation de techniques d'assimilation variationnelle de données. Pour l'analyse de données VHSR, nous proposons des descripteurs spécifiques permettant de caractériser les motifs texturés que l'on a à manipuler. Ces descripteurs sont ensuite utilisés pour résoudre différents problèmes d'analyse de données VHSR tels que la segmentation, la classification, la détection de fronts texturés ou encore l'estimation de l'orientation. Enfin, un chapitre est consacré à la détection de changements où nous proposons des techniques pour le détection binaire et multi-labels.
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Kpemlie, Emmanuel Kwashi. "Assimilation variationnelle de données de télédétection dans des modèles de fonctionnement des couverts végétaux et du paysage agricole." Phd thesis, Université d'Avignon, 2009. http://tel.archives-ouvertes.fr/tel-00555416.

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La connaissance du microclimat et de l'évapotranspiration ou flux de chaleur latente qui représente la consommation réelle en eau de la culture à l'échelle des parcelles agricoles est une donnée importante pour comprendre le développement des cultures. La plupart des modèles permettant d'estimer l'évapotranspiration sont utilisés sur des surfaces homogènes sans tenir compte des interactions surface - atmosphère et de la variabilité spatiale du domaine agricole. Nous avons utilisé un modèle de couche limite atmosphérique afin de prendre en compte ces interactions. Une approche dite " patchée " permet d'introduire la variabilité spatiale des surfaces dans le modèle à partir des diverses proportions et des caractéristiques des principaux couverts végétaux qui composent le paysage. Une méthode d'assimilation variationnelle a été implémentée afin d'estimer certains paramètres du modèle difficile à connaître précisément. La méthode est basée sur le calcul de l'adjoint du modèle et utilise une température de surface observée par télédétection. L'approche développée est comparée à des approches plus simples considérant chaque type de surface indépendamment, mettant en évidence le rôle de la prise en compte de la variabilité spatiale de la surface sur la simulation du microclimat et des flux de surface
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Книги з теми "Images assimilation"

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Images of otherness in medieval and early modern times: Exclusion, inclusion and assimilation. Berlin: Deutscher Kunstverlag, 2012.

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Majid, Zainab Abdul, ed. Images of the Jawi Peranakan of Penang: Assimilation of the Jawi Peranakan community into the Malay society. [Kuala Lumpur]: Universiti Pendidikan Sultan Idris, 2004.

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Marques, José Alexandre Cardoso. Images de Portugais en France: Immigration et cinéma. Paris, France: L'Harmattan, 2002.

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Novaes, Sylvia Caiuby. Jogo de espelhos: Imagens da representação de si através dos outros. São Paulo, SP, Brasil: Edusp, 1993.

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Pueblos indígenas y extranjeros en la monarquía hispánica: La imagen del otro en tiempos de guerra (siglos XVI-XIX). Madrid: Sílex, 2011.

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Paul's anthropology in context: The image of God, assimilation to God, and tripartite man in ancient Judaism, ancient philosophy and early Christianity. Tübingen: Mohr Siebeck, 2008.

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Berkowitz, Michael. The Jewish self-image: American and British perspectives, 1881-1939. London: Reaktion, 2000.

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The Jewish self-image: American and British perspectives, 1881-1939. London: Reaktion Books, 2000.

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United States. Congress. Senate. Committee on Indian Affairs (1993- ). Reclaiming our image and identity for the next seven generations: Hearing before the Committee on Indian Affairs, United States Senate, One Hundred Twelfth Congress, second session, July 26, 2012. Washington: U.S. Government Printing Office, 2013.

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Brown, Janine Elizabeth. Looking in the mirror, looking in the curriculum: The perpetuation of Eurocentric images. 2007.

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Частини книг з теми "Images assimilation"

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Le Dimet, François-Xavier, Hans E. Ngodock, and Innocent Souopgui. "Images Assimilation: An Ocean Perspective." In Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV), 411–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-77722-7_15.

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Sai Pravallika, M., B. Naga Varun, S. Vasavi, N. Sandeep, M. Jaya Priya, and A. Sashikanth Sarma. "Ocean Wave Modeling from Satellite Images Using Data Assimilation." In Proceedings of International Conference on Data Science and Applications, 77–87. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5120-5_7.

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Jarlan, Lionel, and Gilles Boulet. "Data Assimilation for the Monitoring of Continental Surfaces." In Remote Sensing Imagery, 283–319. Hoboken, USA: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118899106.ch11.

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Mounika, Kalamraju, J. Sheeba Rani, and Gorthi Sai Subrahmanyam. "Stochastic Assimilation Technique for Cloud Motion Analysis." In Proceedings of 2nd International Conference on Computer Vision & Image Processing, 103–13. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7895-8_9.

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Akhter, Shamim, Keigo Sakamoto, Yann Chemin, and Kento Aida. "Parameter-Less GA Based Crop Parameter Assimilation with Satellite Image." In Computational Science and Its Applications – ICCSA 2009, 118–31. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02454-2_9.

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Nakanishi, Tomoko M. "Visualization of 14C-labeled Gas Fixation in a Plant." In Novel Plant Imaging and Analysis, 169–89. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4992-6_5.

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AbstractWe targeted not only the elements we can supply to the nutrient solution but also carbon dioxide gas to visualize the fixation process and the movement of assimilated carbon in a plant. This is another highlight of our study using real-time RI imaging systems (RRIS). The interesting result was that the route of assimilated carbon was different depending on where the fixation took place. In Arabidopsis, most of the metabolites after photosynthesis were transferred to the tip of the main internode and roots when 14CO2 gas was fixed and photosynthates were produced at rosette leaves, whereas most of the metabolites moved to the tip of the branch internode and hardly moved down to the roots when 14CO2 gas was supplied to the aboveground parts of the plant other than rosette leaves. Interestingly, it was possible to visualize and trace which tissue performed the fixation of 14CO2 gas, i.e., carbon could be traced from the fixation site in tissue to tissue formation. However, especially in the case of 14C imaging, image analysis should be carefully performed because of the self-absorption of the β-rays in tissue. To image 14CO2 gas fixation in larger samples, approximately 50 cm in height, a plastic scintillator was introduced, and the assimilation process of the gas was visualized for rice and maize.
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Vidard, A., and O. Titaud. "Assimilation of images." In Advanced Data Assimilation for Geosciences, 371–94. Oxford University Press, 2014. http://dx.doi.org/10.1093/acprof:oso/9780198723844.003.0016.

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Raju, Anand, and Shanthi Thirunavukkarasu. "Convolutional Neural Network Demystified for a Comprehensive Learning with Industrial Application." In Dynamic Data Assimilation - Beating the Uncertainties. IntechOpen, 2020. http://dx.doi.org/10.5772/intechopen.92091.

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In the recent past of time, numerous investigators have driven on and subsidized novelties to image classification methods. In this chapter, an introduction to image classification scheme and their types is offered. Image classification discovers its application in a variety of fields, to name a few, judgment of diseases, finding and identification of faults, classification of nutrition goods based on superiority, valuation of usual capitals and conservation pollution, education of land use and land cover from remote sensing satellite images, character identification and detection in optical character reader, face recognition, object detection, and so on. Automatic image classification schemes found on actual algorithms deliver high accuracy and exactness in recognizing object/features. Convolution neural network is a superior genre of neural network that requires minimal preprocessing. The ability of the convolutional neural network (CNN) to understand the visual content of the input image makes its suitable for recognizing minute variation between the classes. This power of the CNN makes it a good choice to address image classification problems with multi-classes. So, in this chapter, the entire flow of CNN’s architecture with different industrial applications will be discussed.
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Eichhorn, N., and H. Kiesewetter. "A NEW APPROACH FOR IDENTIFICATION AND ASSIMILATION OF POLYGONAL OBJECTS." In Computer Analysis of Images and Patterns, 172–76. De Gruyter, 1989. http://dx.doi.org/10.1515/9783112576205-036.

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Hernández, Marisol Hernández, and Marva Angélica Mora Lumbreras. "Characterization of English Through Augmented Reality." In Augmented Reality for Enhanced Learning Environments, 170–92. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-5243-7.ch007.

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Children who begin to learn English usually associate words with images and sounds; this facilitates the assimilation of knowledge and increases their educational interest. This premise grounded this research using augmented reality-based applications designed for people who want to learn English vocabulary. The set of useful terms for students to learn are put together in various categories such as animals, colors, and things. The vocabulary is stored in a database in different formats that are text, 3D image, and audio, which are associated with items containing a vocabulary that represents abstract entities and that are necessary to complement the learning of the English language. The words are associated with the images and with the corresponding audio in order that the students learn to read, write, listen, and consequently, to pronounce the words. This research is projected for more promising applications based on the multi-lingual teaching process.
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Тези доповідей конференцій з теми "Images assimilation"

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Lingala, Nishanth, Navaratnam Sri Namachchivaya, and Hoong Chieh Yeong. "Data assimilation in multiscale complex systems." In 2015 8th International Workshop on the Analysis of Multitemporal Remote Sensing Images (Multi-Temp). IEEE, 2015. http://dx.doi.org/10.1109/multi-temp.2015.7245762.

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Thomas, Claire, Thomas Corpetti, and Etienne Memin. "Data assimilation for convective cells tracking in MSG images." In 2009 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2009). IEEE, 2009. http://dx.doi.org/10.1109/igarss.2009.5418217.

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Ba, Sileye O., Thomas Corpetti, Bertrand Chapron, and Ronan Fablet. "Variational data assimilation for missing data interpolation in SST images." In IGARSS 2010 - 2010 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2010. http://dx.doi.org/10.1109/igarss.2010.5649206.

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Silva, Thiago M. D., Abelardo Barreto, and Sinesio Pesco. "Uncertainty Quantification in Reservoir History Matching Using the Ensemble Smoother." In XXXII Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sibgrapi.est.2019.8335.

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Ensemble-based methods have been widely used in uncertainty quantification, particularly, in reservoir history matching. The search for a more robust method which holds high nonlinear problems is the focus for this area. The Ensemble Kalman Filter (EnKF) is a popular tool for these problems, but studies have noticed uncertainty in the results of the final ensemble, high dependent on the initial ensemble. The Ensemble Smoother (ES) is an alternative, with an easier impletation and low computational cost. However, it presents the same problem as the EnKF. The Ensemble Smoother with Multiple Data Assimilation (ES-MDA) seems to be a good alternative to these ensemble-based methods, once it assimilates tha same data multiple times. In this work, we analyze the efficiency of the Ensemble Smoother and the Ensemble Smoother with multiple data assimilation in a reservoir histoy matching of a turbidite model with 3 layers, considering permeability estimation and data mismatch.
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Huot, E., I. Herlin, and G. Korotaev. "Assimilation of SST Satellite Images for Estimation of Ocean Circulation Velocity." In 2008 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2008. IEEE, 2008. http://dx.doi.org/10.1109/igarss.2008.4779127.

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Rongyuan, Chen, Chen Rongyuan, Li Shuang, Yang Ran, and Qin QianQing. "Multi-focus Images Fusion Based on Data Assimilation and Genetic Algorithm." In 2008 International Conference on Computer Science and Software Engineering. IEEE, 2008. http://dx.doi.org/10.1109/csse.2008.525.

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Komarov, Alexander S., and Mark Buehner. "Use of sequential SAR images for detecting ice and water in view of data assimilation." In 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS). IEEE, 2017. http://dx.doi.org/10.1109/igarss.2017.8128123.

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Cai, Wenwen, Jinling Song, Jindi Wang, and Zhiqiang Xiao. "Assimilation MODIS and HJ-1 Reflectance Images to Produce NDVI of High Spatial and Temporal Resolution." In 2010 6th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2010. http://dx.doi.org/10.1109/wicom.2010.5601000.

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Watanabe, Shogo, Wataru Fujimoto, Tak Nose, Tsubasa Kodaira, Graham Davies, Daniel Lechner, and Takuji Waseda. "Data Assimilation of the Stereo Reconstructed Wave Fields to a Nonlinear Phase Resolved Wave Model." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-95949.

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Анотація:
Abstract A stereo camera system was installed facing Southeast at the observational tower owned by the University of Tokyo in the Sagami Bay, Japan. The three-dimensional wave fields were reconstructed from the stereo images, which were successfully captured from April 2017 until now, by using an open source software WASS (Waves Acquisition Stereo System). The significant wave heights and periods calculated from the stereo images covering an area of 80 m by 80 m were compared against those derived from the ultra-sonic wave gauge at the tower. Overall, a reasonable agreement is achieved, but the accuracy of the stereo reconstruction degrades with the distance from the camera. Also, the significant wave period derived from stereo imaging tends to be shorter, likely related to the error at high frequencies. The reconstructed wave field will be assimilated into a phase-resolved nonlinear wave model. The ensemble Higher Order Spectral simulations and the implementation of the a4DVAR data assimilation scheme, allowed us to substantially extend the estimated wave field beyond the stereo imaging domain. A field campaign with an ADCP in the field of view of the stereo camera and two surface wave buoys outside of the view were conducted for validation.
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Trieschmann, Olaf, Thomas Hunsaenger, Lars Tufte, and Ulrich Barjenbruch. "Data assimilation of an airborne multiple-remote-sensor system and of satellite images for the North Sea and Baltic Sea." In Remote Sensing, edited by Charles R. Bostater, Jr. and Rosalia Santoleri. SPIE, 2004. http://dx.doi.org/10.1117/12.514023.

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