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Artigos de revistas sobre o assunto "Geodesic distances"

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Li, Yue, Logan Numerow, Bernhard Thomaszewski e Stelian Coros. "Differentiable Geodesic Distance for Intrinsic Minimization on Triangle Meshes". ACM Transactions on Graphics 43, n.º 4 (19 de julho de 2024): 1–14. http://dx.doi.org/10.1145/3658122.

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Computing intrinsic distances on discrete surfaces is at the heart of many minimization problems in geometry processing and beyond. Solving these problems is extremely challenging as it demands the computation of on-surface distances along with their derivatives. We present a novel approach for intrinsic minimization of distance-based objectives defined on triangle meshes. Using a variational formulation of shortest-path geodesics, we compute first and second-order distance derivatives based on the implicit function theorem, thus opening the door to efficient Newton-type minimization solvers. We demonstrate our differentiable geodesic distance framework on a wide range of examples, including geodesic networks and membranes on surfaces of arbitrary genus, two-way coupling between hosting surface and embedded system, differentiable geodesic Voronoi diagrams, and efficient computation of Karcher means on complex shapes. Our analysis shows that second-order descent methods based on our differentiable geodesics outperform existing first-order and quasi-Newton methods by large margins.
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Guzmán Naranjo, Matías, e Gerhard Jäger. "Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology". Open Research Europe 3 (21 de junho de 2023): 104. http://dx.doi.org/10.12688/openreseurope.16141.1.

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It is common for people working on linguistic geography, language contact and typology to make use of some type of distance metric between lects. However, most work so far has either used Euclidean distances, or geodesic distance, both of which do not represent the real separation between communities very accurately. This paper presents two datasets: one on walking distances and one on topographic distances between over 8700 lects across all macro-areas. We calculated walking distances using Open Street Maps data, and topographic distances using digital elevation data. We evaluate these distances. We evaluate these distance metrics on three case studies and show that topographic distance tends to outperform the other distance metrics, but geodesic distances can be used as an adequate approximation in some cases.
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Mejia-Parra, Daniel, Jairo R. Sánchez, Jorge Posada, Oscar Ruiz-Salguero e Carlos Cadavid. "Quasi-Isometric Mesh Parameterization Using Heat-Based Geodesics and Poisson Surface Fills". Mathematics 7, n.º 8 (17 de agosto de 2019): 753. http://dx.doi.org/10.3390/math7080753.

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In the context of CAD, CAM, CAE, and reverse engineering, the problem of mesh parameterization is a central process. Mesh parameterization implies the computation of a bijective map ϕ from the original mesh M ∈ R 3 to the planar domain ϕ ( M ) ∈ R 2 . The mapping may preserve angles, areas, or distances. Distance-preserving parameterizations (i.e., isometries) are obviously attractive. However, geodesic-based isometries present limitations when the mesh has concave or disconnected boundary (i.e., holes). Recent advances in computing geodesic maps using the heat equation in 2-manifolds motivate us to revisit mesh parameterization with geodesic maps. We devise a Poisson surface underlying, extending, and filling the holes of the mesh M. We compute a near-isometric mapping for quasi-developable meshes by using geodesic maps based on heat propagation. Our method: (1) Precomputes a set of temperature maps (heat kernels) on the mesh; (2) estimates the geodesic distances along the piecewise linear surface by using the temperature maps; and (3) uses multidimensional scaling (MDS) to acquire the 2D coordinates that minimize the difference between geodesic distances on M and Euclidean distances on R 2 . This novel heat-geodesic parameterization is successfully tested with several concave and/or punctured surfaces, obtaining bijective low-distortion parameterizations. Failures are registered in nonsegmented, highly nondevelopable meshes (such as seam meshes). These cases are the goal of future endeavors.
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WANG, SONGJING, ZHOUYU YU e LIFENG XI. "AVERAGE GEODESIC DISTANCE OF SIERPINSKI GASKET AND SIERPINSKI NETWORKS". Fractals 25, n.º 05 (4 de setembro de 2017): 1750044. http://dx.doi.org/10.1142/s0218348x1750044x.

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The average geodesic distance is concerned with complex networks. To obtain the limit of average geodesic distances on growing Sierpinski networks, we obtain the accurate value of integral in terms of average geodesic distance and self-similar measure on the Sierpinski gasket. To provide the value of integral, we find the phenomenon of finite pattern on integral inspired by the concept of finite type on self-similar sets with overlaps.
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Jenčová, Anna. "Geodesic distances on density matrices". Journal of Mathematical Physics 45, n.º 5 (maio de 2004): 1787–94. http://dx.doi.org/10.1063/1.1689000.

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Guzmán Naranjo, Matías, e Gerhard Jäger. "Euclide, the crow, the wolf and the pedestrian: distance metrics for linguistic typology". Open Research Europe 3 (2 de julho de 2024): 104. http://dx.doi.org/10.12688/openreseurope.16141.2.

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It is common for people working on linguistic geography, language contact and typology to make use of some type of distance metric between lects. However, most work so far has either used Euclidean distances, or geodesic distance, both of which do not represent the real separation between communities very accurately. This paper presents two datasets: one on walking distances and one on topographic distances between over 8700 lects across all macro-areas. We calculated walking distances using Open Street Maps data, and topographic distances using digital elevation data. We evaluate these distance metrics on three case studies and show that from the four distances, the topographic and geodesic distances showed the most consistent performance across datasets, and would be likely to be reasonable first choices. At the same time, in most cases, the Euclidean distances were not much worse than the other distances, and might be a good enough approximation in cases for which performance is critical, or the dataset cover very large areas, and the point-location information is not very precise.
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BORGELT, MAGDALENE G., MARC VAN KREVELD e JUN LUO. "GEODESIC DISKS AND CLUSTERING IN A SIMPLE POLYGON". International Journal of Computational Geometry & Applications 21, n.º 06 (dezembro de 2011): 595–608. http://dx.doi.org/10.1142/s0218195911003822.

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Let P be a simple polygon of n vertices and let S be a set of N points lying in the interior of P. A geodesic diskGD(p,r) with center p and radius r is the set of points in P that have a geodesic distance ≤ r from p (where the geodesic distance is the length of the shortest polygonal path connection that lies in P). In this paper we present an output sensitive algorithm for finding all N geodesic disks centered at the points of S, for a given value of r. Our algorithm runs in [Formula: see text] time, for some constant c and output size k. It is the basis of a cluster reporting algorithm where geodesic distances are used.
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Hino, Masanori. "Geodesic Distances and Intrinsic Distances on Some Fractal Sets". Publications of the Research Institute for Mathematical Sciences 50, n.º 2 (2014): 181–205. http://dx.doi.org/10.4171/prims/129.

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Mahdi, Hussein Alwan. "A MODIFIED METHOD FOR DETERMINATION OF SCALE FACTOR OF THE PROJECTED GEODESIC". Journal of Engineering 12, n.º 03 (1 de setembro de 2006): 882–95. http://dx.doi.org/10.31026/j.eng.2006.03.31.

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Conformal projection is one of the most important aspects that geodesy dealing with. Thedetermination of the scale factors in the meridian, the parallel and projected geodesic directions are thefinal result of the conformal projection. Methods for determining the scale factors in the meridian andthe parallel directions have a quite sufficient accuracy. While methods for determining the projectedgeodesic have different accuracy and computation complicity.This research adopts a modified method for computing the exact value of scale factor ingeodesic direction. In this method the scale factor is obtained by determining the true and projecteddistances of the geodetic line. In the traditional methods for determining the projected distance it isusual to use the 1/3 Simpson's rule in the computations while the modified method the 3/8 Simpson'srule is used.Computations and mathematical tests were carried out to obtain the scale factors using thetraditional methods and comparison was made with modified method.By applying the developed method and the traditional methods to calculate the scale factor, it wasfound that the modified method is more accurate and the projected distances can be obtained exactly.
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Noyel, Guillaume, Jesús Angulo e Dominique Jeulin. "FAST COMPUTATION OF ALL PAIRS OF GEODESIC DISTANCES". Image Analysis & Stereology 30, n.º 2 (30 de junho de 2011): 101. http://dx.doi.org/10.5566/ias.v30.p101-109.

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Computing an array of all pairs of geodesic distances between the pixels of an image is time consuming. In the sequel, we introduce new methods exploiting the redundancy of geodesic propagations and compare them to an existing one. We show that our method in which the source point of geodesic propagations is chosen according to its minimum number of distances to the other points, improves the previous method up to 32 % and the naive method up to 50 % in terms of reduction of the number of operations.
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Teses / dissertações sobre o assunto "Geodesic distances"

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Oliveira, Guilherme do Nascimento. "Procedural textures mapping using geodesic distances". reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2011. http://hdl.handle.net/10183/34767.

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O mapeamento de texturas é uma técnica bastante importante para adicionar detalhamento a modelos geométricos. O mapeamento de texturas baseadas em imagens costuma ser a abordagem preferida, mas faz uso de imagens pré-computadas que são mais adequadas à representação de padrões estáticos. Por outro lado, texturas procedurais oferecem uma alternativa que depende de funções para descrever os padrões das texturas. Elas garantem mais flexibilidade na definição dos padrões em cenas dinâmicas, tendo ainda uma representação mais compacta e dando um maior controle da aparência da textura através do ajuste de parâmetros. Quando mapeadas por coordenadas 3D, as texturas procedurais não consideram a forma da superfície domodelo, e com coordenadas 2D torna-se necessária a definição dessas coordenadas de forma coerente, que, em modelos complexos ,não é uma tarefa simples. Neste trabalho nós introduzimos o leitor às texturas procedurais e ao mapeamento de texturas, então apresentamos GeoTextures, uma nova abordagem que faz uso de distâncias geodésicas definidas com base em múltiplos pontos de origem sobre a superfície do modelo. As distâncias geodésicas são passadas como parâmetros que permitem que a textura procedural se adeqüe ao relevo do modelo texturizado. Nós validamos a proposta ao usar alguns exemplos de texturas procedurais aplicadas em tempo real na texturização de superfícies complexas, mudando tanto a textura do modelo como a forma, através do uso de tesselagem em hardware.
Texture mapping is an important technique to add detail to geometric models. Imagebased texture mapping is the preferred approach but employs pre-computed images, which are better suited for static patterns. On the other hand, procedural-based texture mapping offers an alternative that rely on functions to describe texturing patterns. This allows more flexibility to define patterns in dynamic scenes, while also having a more compact representation and more control for parametric adjustments on the texture visual appearance. When mapped with 3D coordinates, the procedural textures do not consider the model surface, and with 2D mapping the coordinates must be defined in a coherent way, which for complex models is not an easy task. In this work we give a introduction to procedural texturing and texture mapping, and introduce GeoTextures, an original approach that uses geodesic distance defined from multiple sources at different locations over the surface of the model. The geodesic distance is passed as a parameter that allows the shape of the model to be considered in the definition of the procedural texture. We validate the proposal using procedural textures that are applied in real-time to complex surfaces, and show examples that change both the shading of the models, as well as their shape using hardware-based tessellation.
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Bertrand, Théo. "Méthodes géodésiques et apprentissage pour l’imagerie de microscopie par localisation ultrasonore". Electronic Thesis or Diss., Université Paris sciences et lettres, 2024. http://www.theses.fr/2024UPSLD024.

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La méthode de Microscopie par Localisation Ultrasonore (ULM) est une nouvelle méthode d'imagerie médicale super-résolue qui permet d'outrepasser le compromis précision/distance de pénétration dans les tissus pour l'imagerie du réseau vasculaire. Ce nouveau type d'images pose de nouveaux enjeux mathématiques, notamment pour la segmentation et l'analyse de ses images, étapes nécessaires pour arriver à des méthodes pour le diagnostic. Notre travail se positionne à l'intersection des méthodes géodésiques et des méthodes de Machine Learning. Dans cette thèse nous apportons trois contributions. Une première de ces contributions est centrée autour des contraintes liées aux images ULM et propose le tracking de l'entièreté de l'arbre vasculaire en passant par la détection des point-clés des vaisseaux sanguins apparaissant sur l'image. La deuxième contribution de cette thèse porte sur l'apprentissage de la définition de métriques Riemanniennes pour traiter des tâches de segmentation sur des données d'IRM cérébraux et d'images du fond de l'œil. La dernière partie de notre travail porte sur un problème inverse pour la reconstruction de trajectoires d'agents de contraste dans des images médicales dans le contexte de la super-résolution sans-grille
Ultrasound Localization Microscopy is a new method in super-resolved Medical Imaging that allow us to overcome compromise between precision and penetration distance in the tissues for the imaging of the vascular network. This new type of images raises new mathematical questions, especially for the segmentaton and analysis, necessary steps to achieve medical diagnostic of patients. Our work is positioned at the intersection of geodesic and Machine Learning methods. In this thesis, we make three contributions. The first of these is centered on the constraints linked to ULM images and proposes the tracking of the entire vascular tree through the detection of key points of blood vessels appearing on the image. The second contribution of this thesis deals with learning to define Riemannian metrics to handle segmentation tasks on brain MRI data and eye fundus images. The final part of our work focuses on an inverse problem for reconstructing contrast agent trajectories in medical images in the context of grid-free super-resolution
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Nilsson, Ola. "Level-set methods and geodesic distance functions /". Norrköping : Department of Science and Technology, Linköping University, 2009. http://www.bibl.liu.se/liupubl/disp/disp2009/tek1275s.pdf.

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Wang, Rui, e 王睿. "Medial axis simplification based on global geodesic slope and accumulated hyperbolic distance". Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48330139.

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The medial axis is an important shape representation and the computation of the medial axis is a fundamental research problem in computer graphics. Practically, the medial axis is widely used in various aspects of computer graphics, such as shape analysis, image segmentation, skeleton extraction and mesh generation and so forth. However, the applications of the medial axis have been limited by its sensitivity to boundary perturbations. This characteristic may lead to a number of noise branches and increase the complexity of the medial axis. To solve the sensitivity problem, it is critical to simplify the medial axis. This thesis first investigates the algorithms for computing medial axes of different input shapes. Several algorithms for the filtration of medial axes are then reviewed, such as the local importance measurement algorithms, boundary smoothness algorithms, and the global algorithms. Two novel algorithms for the simplification of the medial axis are proposed to generate a stable and simplified medial axis as well as its reconstructed boundary. The developed Global Geodesic Slope(GGS) algorithm for the medial axis simplification is based on the global geodesic slope defined in this thesis, which combines the advantages of the global and the local algorithms. The GGS algorithm prunes the medial axis according to local features as well as the relative size of the shape. It is less sensitive to boundary noises than the local algorithms, and can maintain the features of the shape in highly concave regions while the global algorithms may not. The other simplification algorithm we propose is the Accumulated Hyperbolic Distance(AHD) algorithm. It directly uses the evaluation criterion of the error, accumulated hyperbolic distance defined in this thesis, as the pruning measurement in the filtration process. It guarantees the upper bound of the error between the reconstructed shape and the original one within the defined threshold. The AHD algorithm avoids sudden changes of the reconstructed shape as the defined threshold changes.
published_or_final_version
Computer Science
Master
Master of Philosophy
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Lu, Shi-Jian. "The significance of atmospheric effects in electronic distance measurement". Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278369.

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Brandão, Artur Caldas. "Possibilidade de emprego de um campo de pontos planimetrico como definidor de um comparador de distancias colineares". reponame:Repositório Institucional da UFPR, 1996. http://hdl.handle.net/1884/48609.

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Orientador: Quintino Dalmolin
Co-orientador: Tarcisio Ferreira Silva
Dissertação (mestrado) - Universidade Federal do Paraná
Resumo: O procedimento clássico usado para determinar as distâncias interpilares de uma linha base multipilar para calibração de distanciômetros, consiste em avaliar essas distâncias diretamente, usando equipamentos de alta precisão. Nesse caso, a precisão final das distâncias interpilares fica limitada à precisão do próprio equipamento usado. Neste trabalho, foi desenvolvido um procedimento metodológico para definir as distâncias interpilares de uma linha base a partir de um campo de pontos planimétrico, em que os pontos da linha base foram incluídos. Para tanto, a configuração geométrica do campo de pontos foi adequadamente otimizada através de procedimentos de simulação. Garantiu-se assim que os resultados esperados para a precisão final dos pontos da rede fossem obtidos antes mesmo do trabalho de campo ser conduzido. O programa "NETZ2D" de análise e ajustamento de redes 2D foi usado como ferramenta computacional. Os experimentos realizados no processo de simulação e de medição do campo de pontos, foram conduzidos sobre a linha base da UFPE. Na medição do campo de pontos otimizado, garantiu-se o controle do processo de medição em termos de escolha adequada do período de medição e dos equipamentos. Verificou-se que a metodologia proposta, quando comparado ao procedimento clássico, apresentou vantagens em termos de facilidades de implementação bem como nos resultados obtidos. No experimento realizado, as distâncias interpilares da linha base da UFPE foram definidas com uma precisão cinco vezes maior que a precisão das medidas de distâncias avaliadas no campo de pontos. Por outro lado, resultado final equivalente foi obtido para os pontos da linha base simulando um campo de pontos com um único padrão metrológico de distância.
Abstract: The used classic proceeding to determine the interpillares distancies of one multipillar base line to calibration of eletronic distancies measuring (EDM), consist in to evaluate this distancies directing using equipmenty of high precision. In this case, the finish precision of the interpillares distancies stay limited the precision of proper equipment used. In this work, was developed a metodologic proceeding to define the interpillares distancies of one base line until of the network 2D, in that the points of base line was incluids. To that effect, the geometric configuration of network 2D was adequatement optimized through of proceeding of simulation. Was guaranted that the hoped results to the finish precision of the points of the net have was obtain before the work of field to be conduzed. The program "NETZ2D" of analysis and adjustment of the nets was used how computation instrument. The experiments realized in the simulation and measure process of the network, was conduzed about the base line of UFPE. On the measuring of network optmized, was guaranty the control of the measuring process adequad choose of the time of the measuring and of the equipments. Was verified that the offered metodology, when compared to the classic proceeding, showed advantagies of easilies implementation, as in the results obtained. On the experiment realized, the interpillares distancies of base line of the UFPE was define with one precision five time bigger than the precision o f the measure of the distancies evaluated on network. On the other hand, the equivalent finish result was obtained to the points of the base line, simulating one network with only one standart metrologic of the distance.
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Kohli, Mathieu. "De la notion de courbure géodésique en géométrie sous-Riemannienne". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLX043/document.

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Dans cette thèse, on présente une notion de courbure géodésique pour les courbes lisses horizontales dans une variété sous-Riemannienne de contact, qui indique dans quelle mesure une courbe est différente d'une géodésique. Cette courbure géodésique se présente sous la forme de deux fonctions qui sont toutes deux identiquement nulles le long d'une courbe lisse horizontale si et seulement si cette dernière courbe est une géodésique. Le résultat principal de cette thèse réside dans l'interprétation métrique que l'on donne de ces fonctions de courbure. Cette interprétation consiste à extraire la courbure géodésique des premiers termes de correction dans le développement limité de la distance sous-Riemannienne entre deux points proches le long de la courbe
We present a notion of geodesic curvature for smooth horizontal curves in a contact sub-Riemannian manifold, measuring how far a horizontal curve is from being a geodesic. This geodesic curvature consists in two functions that both vanish along a smooth horizontal curve if and only if this curve is a geodesic. The main result of this thesis is the metric interpretation of these geodesic curvature functions. This interpretation consists in seeing the geodesic curvature functions as the first corrective coefficients in the Taylor expansion of the sub-Riemannian distance between two close points on the curve
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Arcostanzo, Marc. "Rigidité et prolongement au disque d'une distance sur le bord". Université Joseph Fourier (Grenoble), 1994. http://www.theses.fr/1994GRE10216.

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Etant donne une distance d sur le bord d'un disque de dimension deux, nous cherchons dans cette these a prolonger d en une distance sur le disque tout entier, de telle sorte que l'espace metrique obtenu soit un espace de longueur, par exemple une metrique riemannienne ou finslerienne. Le prolongement est dit rigide s'il est unique a isometrie pres. Des resultats de rigidite ont ete obtenus par r. Michel, j. P. Otal et c. B. Croke en se restreignant aux metriques riemanniennes. Nous prouvons ici la rigidite des metriques euclidiennes a singularites coniques de courbures negatives. Nous donnons egalement des exemples de metriques riemanniennes non rigides. Nous montrons ensuite qu'un tel prolongement est entierement determine par la donnee de ses courbes geodesiques, ce qui permet de decrire l'ensemble des solutions du probleme. En imposant des conditions sur la distance sur le bord et le systeme de geodesiques, l'espace de longueur obtenu provient en fait d'une metrique finslerienne ou riemannienne. On obtient finalement un critere pour que deux prolongements ne soient pas isometriques
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Miller, Charles Miller. "THE EFFECT OF DISTANCE DECAY: A STUDY OF AUTOMOTIVE RETAILING". Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/439401.

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Business Administration/Interdisciplinary
D.B.A.
Retail automotive literature that examines how the distance between a retail automotive facility and the prospective purchaser affects market performance is limited. Primary data for this study indicates that distance and purchase in the retail automotive sector move in opposite directions. This study examines similar goods that have high barriers of entry and proposes other methods of increasing market reach. This is a study of the conditions that affect the market performance for imported luxury vehicles. First, is the effect of distance on purchase decisions. Vehicular sales drop the further away a customer is from a car dealership. We call this phenomenon distance decay. Distance decay is defined as: the interaction between two locations declines as the distance between then increases. Secondly, when similar brands are viewed as substitutes, the consumer will choose the brand with the closest automotive service department to their residence or place of employment. Thirdly, door-to-door selling can decrease distance decay. Lastly, pick-up and delivery service can decrease distance decay. Data from 30,936 prospects and individuals who entered, phoned, or emailed a dealership inquiring about purchasing a new Audi were used in the study. These prospects will be categorized by who intended to buy and who actually purchased a car. In addition to the prospects, data from 6,153 individuals who purchased a new Audi from four Audi dealerships in the greater Philadelphia area and from the framed field experiment were used in the study. These categories will then be further labeled by ZIP code and city to determine the effects of distance. Then, possible solutions will be performed on test groups to determine what alternatives from other industries can be used to improve market performance involving long distances.
Temple University--Theses
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Cruz, Barbosa Raúl. "Generative manifold learning for the exploration of partially labeled data". Doctoral thesis, Universitat Politècnica de Catalunya, 2009. http://hdl.handle.net/10803/78053.

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In many real-world application problems, the availability of data labels for supervised learning is rather limited. Incompletely labeled datasets are common in many of the databases generated in some of the currently most active areas of research. It is often the case that a limited number of labeled cases is accompanied by a larger number of unlabeled ones. This is the setting for semi-supervised learning, in which unsupervised approaches assist the supervised problem and vice versa. A manifold learning model, namely Generative Topographic Mapping (GTM), is the basis of the methods developed in this thesis. The non-linearity of the mapping that GTM generates makes it prone to trustworthiness and continuity errors that would reduce the faithfulness of the data representation, especially for datasets of convoluted geometry. In this thesis, a variant of GTM that uses a graph approximation to the geodesic metric is first defined. This model is capable of representing data of convoluted geometries. The standard GTM is here modified to prioritize neighbourhood relationships along the generated manifold. This is accomplished by penalizing the possible divergences between the Euclidean distances from the data points to the model prototypes and the corresponding geodesic distances along the manifold. The resulting Geodesic GTM (Geo-GTM) model is shown to improve the continuity and trustworthiness of the representation generated by the model, as well as to behave robustly in the presence of noise. The thesis then leads towards the definition and development of semi-supervised versions of GTM for partially-labeled data exploration. As a first step in this direction, a two-stage clustering procedure that uses class information is presented. A class information-enriched variant of GTM, namely class-GTM, yields a first cluster description of the data. The number of clusters defined by GTM is usually large for visualization purposes and does not necessarily correspond to the overall class structure. Consequently, in a second stage, clusters are agglomerated using the K-means algorithm with different novel initialization strategies that benefit from the probabilistic definition of GTM. We evaluate if the use of class information influences cluster-wise class separability. A robust variant of GTM that detects outliers while effectively minimizing their negative impact in the clustering process is also assessed in this context. We then proceed to the definition of a novel semi-supervised model, SS-Geo-GTM, that extends Geo-GTM to deal with semi-supervised problems. In SS-Geo-GTM, the model prototypes are linked by the nearest neighbour to the data manifold constructed by Geo-GTM. The resulting proximity graph is used as the basis for a class label propagation algorithm. The performance of SS-Geo-GTM is experimentally assessed, comparing positively with that of an Euclidean distance-based counterpart and that of the alternative Laplacian Eigenmaps method. Finally, the developed models (the two-stage clustering procedure and the semi-supervised models) are applied to the analysis of a human brain tumour dataset (obtained by Nuclear Magnetic Resonance Spectroscopy), where the tasks are, in turn, data clustering and survival prognostic modeling.
Resum de la tesi (màxim 4000 caràcters. Si se supera aquest límit, el resum es tallarà automàticament al caràcter 4000) En muchos problemas de aplicación del mundo real, la disponibilidad de etiquetas de datos para aprendizaje supervisado es bastante limitada. La existencia de conjuntos de datos etiquetados de manera incompleta es común en muchas de las bases de datos generadas en algunas de las áreas de investigación actualmente más activas. Es frecuente que un número limitado de casos etiquetados venga acompañado de un número mucho mayor de datos no etiquetados. Éste es el contexto en el que opera el aprendizaje semi-supervisado, en el cual enfoques no-supervisados prestan ayuda a problemas supervisados y vice versa. Un modelo de aprendizaje de variaciones (manifold learning, en inglés), llamado Mapeo Topográfico Generativo (GTM, en acrónimo de su nombre en inglés), es la base de los métodos desarrollados en esta tesis. La no-linealidad del mapeo que GTM genera hace que éste sea propenso a errores de fiabilidad y continuidad, los cuales pueden reducir la fidelidad de la representación de los datos, especialmente para conjuntos de datos de geometría intrincada. En esta tesis, una extensión de GTM que utiliza una aproximación vía grafos a la métrica geodésica es definida en primer lugar. Este modelo es capaz de representar datos con geometrías intrincadas. En él, el GTM estándar es modificado para priorizar relaciones de vecindad a lo largo de la variación generada. Esto se logra penalizando las divergencias existentes entre las distancias Euclideanas de los datos a los prototipos del modelo y las correspondientes distancias geodésicas a lo largo de la variación. Se muestra que el modelo Geo-GTM resultante mejora la continuidad y fiabilidad de la representación generada y que se comporta de manera robusta en presencia de ruido. Más adelante, la tesis nos lleva a la definición y desarrollo de versiones semi-supervisadas de GTM para la exploración de conjuntos de datos parcialmente etiquetados. Como un primer paso en esta dirección, se presenta un procedimiento de agrupamiento en dos etapas que utiliza información de pertenencia a clase. Una extensión de GTM enriquecida con información de pertenencia a clase, llamada class-GTM, produce una primera descripción de grupos de los datos. El número de grupos definidos por GTM es normalmente grande para propósitos de visualización y no corresponde necesariamente con la estructura de clases global. Por ello, en una segunda etapa, los grupos son aglomerados usando el algoritmo K-means con diferentes estrategias de inicialización novedosas las cuales se benefician de la definición probabilística de GTM. Evaluamos si el uso de información de clase influye en la separabilidad de clase por grupos. Una extensión robusta de GTM que detecta datos atípicos a un tiempo que minimiza de forma efectiva su impacto negativo en el proceso de agrupamiento es evaluada también en este contexto. Se procede después a la definición de un nuevo modelo semi-supervisado, SS-Geo-GTM, que extiende Geo-GTM para ocuparse de problemas semi-supervisados. En SS-Geo-GTM, los prototipos del modelo son vinculados al vecino más cercano a la variación construída por Geo-GTM. El grafo de proximidad resultante es utilizado como base para un algoritmo de propagación de etiquetas de clase. El rendimiento de SS-Geo-GTM es valorado experimentalmente, comparando positivamente tanto con la contraparte de este modelo basada en la distancia Euclideana como con el método alternativo Laplacian Eigenmaps. Finalmente, los modelos desarrollados (el procedimiento de agrupamiento en dos etapas y los modelos semi-supervisados) son aplicados al análisis de un conjunto de datos de tumores cerebrales humanos (obtenidos mediante Espectroscopia de Resonancia Magnética Nuclear), donde las tareas a realizar son el agrupamiento de datos y el modelado de pronóstico de supervivencia.
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Livros sobre o assunto "Geodesic distances"

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Kravchenko, Yuriy. Surveying. ru: INFRA-M Academic Publishing LLC., 2017. http://dx.doi.org/10.12737/textbook_5900a29b032774.83960082.

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The contents of the book corre-sponds to the curriculum of surveying for building schools. Including historical and general information about on geodesy, the basic principles of treatment results of geodetic measurements, information about topographic maps and plans and solutions the problems with their use, description of instruments and methods of measurement of angles, distances and excesses on the earth surface, information about horizontal and vertical geo-detic networks, methods for creat-ing and processing survey geodes-ic networks, types and methods of survey, a description of the meth-ods removal projects in nature, description of the geodetic works in prospecting, designing and con-struction of objects capital con-struction.
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2

Rüeger, J. M. Electronic distance measurement: An introduction. 3a ed. Berlin: Springer-Verlag, 1990.

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3

Rüeger, J. M. Electronic distance measurement: An introduction. 3a ed. Berlin: Springer-Verlag, 1990.

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4

Rüeger, J. M. Electronic distance measurement: An introduction. 3a ed. Berlin: Springer-Verlag, 1990.

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5

Rüeger, J. M. Electronic distance measurement: An introduction. 4a ed. Berlin: Springer, 1996.

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6

Guoqiang, Tang. Studies of extragalactic radio source structure and its effect on geodetic VLBI measurement. Göteborg, Sweden: School of Electrical and Computer Engineering, Chalmers University of Technology, 1988.

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7

Elements of Plane and Spherical Trigonometry: With Their Applications to Heights and Distances Projections of the Sphere, Dialling, Astronomy, the Solution of Equations, and Geodesic Operations. Creative Media Partners, LLC, 2023.

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8

Rüeger, Jean M. Electronic Distance Measurement: An Introduction. Springer London, Limited, 2012.

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9

Rüeger, Jean M. Electronic Distance Measurement: An Introduction. 4a ed. Springer, 1996.

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10

Rueger, Jean M. Electronic Distance Measurement: An Introduction. Springer-Verlag, 1991.

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Capítulos de livros sobre o assunto "Geodesic distances"

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Aiello, Rosario, Francesco Banterle, Nico Pietroni, Luigi Malomo, Paolo Cignoni e Roberto Scopigno. "Compression and Querying of Arbitrary Geodesic Distances". In Image Analysis and Processing — ICIAP 2015, 282–93. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23231-7_26.

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Aflalo, Yonathan, e Ron Kimmel. "Measuring Geodesic Distances via the Uniformization Theorem". In Lecture Notes in Computer Science, 471–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-24785-9_40.

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3

Berretti, S., A. Del Bimbo, P. Pala e F. J. Silva Mata. "Face Recognition by Matching 2D and 3D Geodesic Distances". In Multimedia Content Analysis and Mining, 444–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-73417-8_53.

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Soille, Pierre. "Generalized Geodesic Distances Applied to Interpolation and Shape Description". In Computational Imaging and Vision, 193–200. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-011-1040-2_25.

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Handrich, Sebastian, e Ayoub Al-Hamadi. "Upper-Body Pose Estimation Using Geodesic Distances and Skin-Color". In Advanced Concepts for Intelligent Vision Systems, 150–61. Cham: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-02895-8_14.

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Estévez, Pablo A., Andrés M. Chong, Claudio M. Held e Claudio A. Perez. "Nonlinear Projection Using Geodesic Distances and the Neural Gas Network". In Artificial Neural Networks – ICANN 2006, 464–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11840817_49.

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Datar, Manasi, Ilwoo Lyu, SunHyung Kim, Joshua Cates, Martin A. Styner e Ross Whitaker. "Geodesic Distances to Landmarks for Dense Correspondence on Ensembles of Complex Shapes". In Advanced Information Systems Engineering, 19–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-40763-5_3.

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Handrich, Sebastian, e Ayoub Al-Hamadi. "Full-Body Human Pose Estimation by Combining Geodesic Distances and 3D-Point Cloud Registration". In Advanced Concepts for Intelligent Vision Systems, 287–98. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25903-1_25.

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Bloch, Isabelle. "Fuzzy morphology and fuzzy distances: New definitions and links in both euclidean and geodesic cases". In Fuzzy Logic in Artificial Intelligence, 149–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0095076.

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Hooijberg, Maarten. "Geodetic Arc Distances". In Practical Geodesy, 61–73. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-60584-0_4.

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Trabalhos de conferências sobre o assunto "Geodesic distances"

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Tekir, Selma, Florian Mansmann e Daniel Keim. "Geodesic distances for web document clustering". In 2011 Ieee Symposium On Computational Intelligence And Data Mining - Part Of 17273 - 2011 Ssci. IEEE, 2011. http://dx.doi.org/10.1109/cidm.2011.5949449.

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Li Yang. "Sammon's nonlinear mapping using geodesic distances". In Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004. IEEE, 2004. http://dx.doi.org/10.1109/icpr.2004.1334180.

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Yu Cai, Yanjin Huang e Shugong Zhang. "3D face recognition using weighted geodesic distances". In 2011 International Conference on Transportation and Mechanical & Electrical Engineering (TMEE). IEEE, 2011. http://dx.doi.org/10.1109/tmee.2011.6199695.

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Meng, Deyu, Zongben Xu, Nannan Gu e Mingwei Dai. "Estimating geodesic distances on locally linear patches". In 2007 IEEE International Symposium on Signal Processing and Information Technology. IEEE, 2007. http://dx.doi.org/10.1109/isspit.2007.4458006.

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Góes, Daniel A., e Nelson D. A. Mascarenhas. "Low-Dose Computed Tomography Filtering Using Geodesic Distances". In Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação, 2020. http://dx.doi.org/10.5753/sibgrapi.est.2020.12983.

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Due to the concerns related to patient exposure to X-ray, the dosage used in computed tomography must be reduced (Low-dose Computed Tomography - LDCT). One of the effects of LDCT is the degradation in the quality of the final reconstructed image. In this work, we propose a method of filtering LDCT sinograms that are subject to signal-dependent Poisson noise. To filter this type of noise, we use a Bayesian approach, changing the Non-local Means (NLM) algorithm to use geodesic stochastic distances for Gamma distribution, the conjugate prior to Poisson, as a similarity metric between each projection point. Among the geodesic distances evaluated, we found a closed solution for the Shannon entropy for Gamma distributions. We compare our method with the following methods based on NLM: PoissonNLM, Stochastic Poisson NLM, Stochastic Gamma NLM and the original NLM after Anscombe transform. We also compare with BM3D after Anscombe transform. Comparisons are made on the final images reconstructed by the Filtered-Back Projection (FBP) and Projection onto Convex Sets (POCS) methods using the metrics PSNR and SSIM.
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Edelstein, Michal, Nestor Guillen, Justin Solomon e Mirela Ben-Chen. "A Convex Optimization Framework for Regularized Geodesic Distances". In SIGGRAPH '23: Special Interest Group on Computer Graphics and Interactive Techniques Conference. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3588432.3591523.

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Twining, C., S. Marsland e C. Taylor. "Measuring Geodesic Distances on the Space of Bounded Diffeomorphisms". In British Machine Vision Conference 2002. British Machine Vision Association, 2002. http://dx.doi.org/10.5244/c.16.83.

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Oda, Takuya, Yuichi Itoh, Wataru Nakai, Katsuhiro Nomura, Yoshifumi Kitamura e Fumio Kishino. "Interactive skeleton extraction for 3D animation using geodesic distances". In ACM SIGGRAPH 2006 Research posters. New York, New York, USA: ACM Press, 2006. http://dx.doi.org/10.1145/1179622.1179632.

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Berretti, Stefano, Alberto Del Bimbo, Pietro Pala e Francisco J. Silva Mata. "Geodesic Distances for 3D-3D and 2D-3D Face Recognition". In Multimedia and Expo, 2007 IEEE International Conference on. IEEE, 2007. http://dx.doi.org/10.1109/icme.2007.4284950.

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Ring, Dan, e François Pitie. "Feature-Assisted Sparse to Dense Motion Estimation Using Geodesic Distances". In 2009 13th International Machine Vision and Image Processing Conference. IEEE, 2009. http://dx.doi.org/10.1109/imvip.2009.9.

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Relatórios de organizações sobre o assunto "Geodesic distances"

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Memoli, Facundo, e Guillermo Sapiro. Distance Functions and Geodesics on Points Clouds. Fort Belvoir, VA: Defense Technical Information Center, janeiro de 2005. http://dx.doi.org/10.21236/ada437158.

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Jin, Zheming. A Study of Geodesic Distance Kernel on an Integrated GPU. Office of Scientific and Technical Information (OSTI), novembro de 2019. http://dx.doi.org/10.2172/1576565.

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Dudnikov, V. Yu. Electronic course for distance learning "Basics of geodesy and topography" (UGSN 21.00.00 "Applied geology, mining, oil and gas and geodesy"). Science and Innovation Center Publishing House, 2016. http://dx.doi.org/10.12731/dudnikov.11082016.22085.

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