Academic literature on the topic 'Geometry priors'
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Journal articles on the topic "Geometry priors"
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Guo, Xiaomeng, Li Yi, Hang Zou, and Yining Gao. "Generative Facial Prior for Large-Factor Blind Face Super-Resolution." Journal of Physics: Conference Series 2078, no. 1 (November 1, 2021): 012045. http://dx.doi.org/10.1088/1742-6596/2078/1/012045.
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Abstract Most existing face super-resolution (SR) methods are developed based on an assumption that the degradation is fixed and known (e.g., bicubic down sampling). However, these methods suffer a severe performance drop in various unknown degradations in real-world applications. Previous methods usually rely on facial priors, such as facial geometry prior or reference prior, to restore realistic face details. Nevertheless, low-quality inputs cannot provide accurate geometric priors while high-quality references are often unavailable, which limits the use of face super-resolution in real-world scenes. In this work, we propose GPLSR which used the rich priors encapsulated in the pre-trained face GAN network to perform blind face super-resolution. This generative facial priori is introduced into the face super-resolution process through channel squeeze-and-excitation spatial feature transformation layer (SE-SFT), which makes our method achieve a good balance between realness and fidelity. Moreover, GPLSR can restores facial details with single forward pass because of powerful generative facial prior information. Extensive experiment shows that when the magnification factor is 16, this method achieves better performance than existing techniques in both synthetic and real datasets.
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Goldman, Yehonatan, Ehud Rivlin, and Ilan Shimshoni. "Robust epipolar geometry estimation using noisy pose priors." Image and Vision Computing 67 (November 2017): 16–28. http://dx.doi.org/10.1016/j.imavis.2017.09.006.
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Huang, Han, Yulun Wu, Junsheng Zhou, Ge Gao, Ming Gu, and Yu-Shen Liu. "NeuSurf: On-Surface Priors for Neural Surface Reconstruction from Sparse Input Views." Proceedings of the AAAI Conference on Artificial Intelligence 38, no. 3 (March 24, 2024): 2312–20. http://dx.doi.org/10.1609/aaai.v38i3.28005.
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Recently, neural implicit functions have demonstrated remarkable results in the field of multi-view reconstruction. However, most existing methods are tailored for dense views and exhibit unsatisfactory performance when dealing with sparse views. Several latest methods have been proposed for generalizing implicit reconstruction to address the sparse view reconstruction task, but they still suffer from high training costs and are merely valid under carefully selected perspectives. In this paper, we propose a novel sparse view reconstruction framework that leverages on-surface priors to achieve highly faithful surface reconstruction. Specifically, we design several constraints on global geometry alignment and local geometry refinement for jointly optimizing coarse shapes and fine details. To achieve this, we train a neural network to learn a global implicit field from the on-surface points obtained from SfM and then leverage it as a coarse geometric constraint. To exploit local geometric consistency, we project on-surface points onto seen and unseen views, treating the consistent loss of projected features as a fine geometric constraint. The experimental results with DTU and BlendedMVS datasets in two prevalent sparse settings demonstrate significant improvements over the state-of-the-art methods.
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PRANEETH RACHARLA, SHARATH CHANDRA YERVA, SANJAY RAVULA, and DR.P.ILA CHANDANA KUMARI. "IMAGE RECONSTRUCTION OF OLD DAMAGED PHOTOS." international journal of engineering technology and management sciences 8, no. 3 (2024): 70–74. http://dx.doi.org/10.46647/ijetms.2024.v08i03.009.
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In order to restore accurate and realistic details, blind face restoration often uses facial priors, such as a reference prior or a facial geometry prior. The applicability to real-world situations is, however, constrained by the inaccessibility of high quality references and the inability of very low-quality inputs to provide accurate geometric prior. In this paper, we present a GFP-GAN for blind face restoration that takes advantage of rich and varied priors included in a pre-trained face GAN. By the use of spatial feature transform layers, this Generative Facial Prior (GFP) is incorporated into the face restoration process, enabling our method to successfully strike a compromise between realism and fidelity. Whereas GAN inversion methods require image-specific tweaking at inference, our GFP-GAN could simultaneously restore facial details and enhance colours with just a single forward pass because of the powerful generative facial prior and delicate designs. Many tests demonstrate that, on both synthetic and realworld datasets, our technique outperforms earlier art.
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Nguyen, Ngoc Hung. "Optimal Geometry Analysis for Target Localization With Bayesian Priors." IEEE Access 9 (2021): 33419–37. http://dx.doi.org/10.1109/access.2021.3056440.
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Langlois, Thomas A., Nori Jacoby, Jordan W. Suchow, and Thomas L. Griffiths. "Serial reproduction reveals the geometry of visuospatial representations." Proceedings of the National Academy of Sciences 118, no. 13 (March 26, 2021): e2012938118. http://dx.doi.org/10.1073/pnas.2012938118.
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An essential function of the human visual system is to locate objects in space and navigate the environment. Due to limited resources, the visual system achieves this by combining imperfect sensory information with a belief state about locations in a scene, resulting in systematic distortions and biases. These biases can be captured by a Bayesian model in which internal beliefs are expressed in a prior probability distribution over locations in a scene. We introduce a paradigm that enables us to measure these priors by iterating a simple memory task where the response of one participant becomes the stimulus for the next. This approach reveals an unprecedented richness and level of detail in these priors, suggesting a different way to think about biases in spatial memory. A prior distribution on locations in a visual scene can reflect the selective allocation of coding resources to different visual regions during encoding (“efficient encoding”). This selective allocation predicts that locations in the scene will be encoded with variable precision, in contrast to previous work that has assumed fixed encoding precision regardless of location. We demonstrate that perceptual biases covary with variations in discrimination accuracy, a finding that is aligned with simulations of our efficient encoding model but not the traditional fixed encoding view. This work demonstrates the promise of using nonparametric data-driven approaches that combine crowdsourcing with the careful curation of information transmission within social networks to reveal the hidden structure of shared visual representations.
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Bernardo, Jose M. "[The Geometry of Asymptotic Inference]: Comment: On Multivariate Jeffreys' Priors." Statistical Science 4, no. 3 (August 1989): 227–29. http://dx.doi.org/10.1214/ss/1177012483.
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Zhang, Xin, and Andrew Curtis. "Bayesian full-waveform inversion with realistic priors." GEOPHYSICS 86, no. 5 (August 30, 2021): A45—A49. http://dx.doi.org/10.1190/geo2021-0118.1.
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Seismic full-waveform inversion (FWI) uses full seismic records to estimate the subsurface velocity structure. This requires a highly nonlinear and nonunique inverse problem to be solved; therefore, Bayesian methods have been used to quantify uncertainties in the solution. Variational Bayesian inference uses optimization to efficiently provide solutions. However, previously the method has only been applied to a transmission FWI problem and with strong prior information imposed on the velocity such as is never available in practice. We have found that the method works well in a seismic reflection setting and with realistically weak prior information, representing the type of problem that occurs in reality. We conclude that the method can produce high-resolution images and reliable uncertainties using data from standard reflection seismic acquisition geometry, realistic nonlinearity, and practically achievable prior information.
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Zhou, Zhongxian, Jianchen Liu, Miaomiao Feng, and Yuwei Cong. "Surveillance Video Georeference Method Based on Real Scene Model with Geometry Priors." Remote Sensing 15, no. 17 (August 28, 2023): 4217. http://dx.doi.org/10.3390/rs15174217.
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With the comprehensive promotion of digital construction in China, cameras scattered throughout the country are of great significance in obtaining first-hand data. However, their potential role is limited due to the lack of georeference information on current surveillance cameras. Provided surveillance camera images and real scenes are combined and given georeference information, this problem can be solved, allowing cameras to generate significant social benefits. This article proposed an accurate registration method based on misalignment calibration and least squares matching between real scene and surveillance camera images to address this issue. Firstly, it is necessary to convert the navigation coordinate system from which cameras obtain data to the photogrammetric coordinate system and then solve for the misalignment and internal orientation elements of the camera. Then, accurate registration is achieved using the least squares matching on pyramid images. The experiment obtained surrounding image data of two common scenes with lens pitch angles of 45°, 55°, 65°, 75°, and 85° using the surveillance camera and obtained a 3D real scene model of each scene using a low-altitude aircraft. The experiment results show that the proposed method in this paper can achieve the expected goals of accurately matching real scene and surveillance camera images and assigning georeference information. Through extensive data analysis, the success rate and accuracy rate of registration are 98.1% and 97.06%, respectively.
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Lee, Se Yoon. "The Use of a Log-Normal Prior for the Student t-Distribution." Axioms 11, no. 9 (September 8, 2022): 462. http://dx.doi.org/10.3390/axioms11090462.
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It is typically difficult to estimate the number of degrees of freedom due to the leptokurtic nature of the Student t-distribution. Particularly in studies with small sample sizes, special care is needed concerning prior choice in order to ensure that the analysis is not overly dominated by any prior distribution. In this article, popular priors used in the existing literature are examined by characterizing their distributional properties on an effective support where it is desirable to concentrate on most of the prior probability mass. Additionally, we suggest a log-normal prior as a viable prior option. We show that the Bayesian estimator based on a log-normal prior compares favorably to other Bayesian estimators based on the priors previously proposed via simulation studies and financial applications.
Dissertations / Theses on the topic "Geometry priors"
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Osorio, José Manuel. "Kant and the Problem of Geometry." Pontificia Universidad Católica del Perú, 2014. http://repositorio.pucp.edu.pe/index/handle/123456789/119539.
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Geometry is an a priori science. However, its apriority is saddled with problems. The aim of this paper will be to show 1) how Kant understands that the contents of geometry are synthetic a priori judgments in the Critique of Pure Reason, and 2) if it’s still relevant to study Kant’s theory of geometry after the challenges posed by non-Euclidian theories of space. With respect to point 1: Kant understands geometry as the discipline that objectifies the pure intuition of space. Every geometric concept is built upon the pure intuition of space through a synthetic ostensive process. Furthermore, the pure intuition of space is the form of external experiences. Thus, geometry and external phenomena share a common ground – pure space. This common ground is what provides an answer to the question of the possibility of mathematics as a universal and a priori science. With respect to point 2: the relevance of studying Kant’s theory of geometry lies not only in the fact that geometry can serve as an example to philosophy based on the fact that it establishes its propositions a priori, but also because the object-study of geometry – the pure intuition of space– forces the reader to review Kant’s thoughts about sensibility and its relation to space. The analysis of Kant’s theory of geometry then amounts to studying Kant’s theory of sensibility.Para Kant la geometría es una disciplina matemática que contiene proposiciones y juicios sintéticos a priori. Sin embargo, esta afirmación no se encuentra libre de problemas. La intención del artículo será mostrar 1) cómo entiende Kant la apodicticidad, universalidad y sinteticidad de la geometría en la Crítica de la razón pura; y 2) qué relevancia tiene hoy en día estudiar la teoría kantiana de la geometría luego de la superación de la teoría euclidiana del espacio. Con respecto a (1): Kant entiende a la geometría como la ciencia que objetiva la intuición pura del espacio. Todo concepto geométrico se construye en la intuición del espacio mediante un proceso sintético que exhibe la figura geométrica. Además, la intuición pura del espacio es la forma del sentido externo. Por tanto, los objetos geométricos y los fenómenos externos comparten un territorio común: el espacio como intuición pura. Este aspecto común garantiza la universidad de la geometría. Con respecto a (2): la importancia de estudiar la teoría kantiana de la geometría no solo radica en que esta disciplina determina a priori su objeto y por tanto sirve de ejemplo a la filosofía, sino que la comprensión del objeto de la geometría, el espacio como intuición pura, nos obliga a pasar revista a lo qué entiende Kant por sensibilidad y su relación con el espacio. El estudio de la sensibilidad obliga a Kant a repensar qué se entiende por espacio y, con ello, qué se entiende por geometría. El análisis de la teoría kantiana de la geometría, entonces, equivale al estudio de la teoría kantiana de la sensibilidad.
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Hold-Geoffroy, Yannick. "Learning geometric and lighting priors from natural images." Doctoral thesis, Université Laval, 2018. http://hdl.handle.net/20.500.11794/31264.
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Comprendre les images est d’une importance cruciale pour une pléthore de tâches, de la composition numérique au ré-éclairage d’une image, en passant par la reconstruction 3D d’objets. Ces tâches permettent aux artistes visuels de réaliser des chef-d’oeuvres ou d’aider des opérateurs à prendre des décisions de façon sécuritaire en fonction de stimulis visuels. Pour beaucoup de ces tâches, les modèles physiques et géométriques que la communauté scientifique a développés donnent lieu à des problèmes mal posés possédant plusieurs solutions, dont généralement une seule est raisonnable. Pour résoudre ces indéterminations, le raisonnement sur le contexte visuel et sémantique d’une scène est habituellement relayé à un artiste ou un expert qui emploie son expérience pour réaliser son travail. Ceci est dû au fait qu’il est généralement nécessaire de raisonner sur la scène de façon globale afin d’obtenir des résultats plausibles et appréciables. Serait-il possible de modéliser l’expérience à partir de données visuelles et d’automatiser en partie ou en totalité ces tâches ? Le sujet de cette thèse est celui-ci : la modélisation d’a priori par apprentissage automatique profond pour permettre la résolution de problèmes typiquement mal posés. Plus spécifiquement, nous couvrirons trois axes de recherche, soient : 1) la reconstruction de surface par photométrie, 2) l’estimation d’illumination extérieure à partir d’une seule image et 3) l’estimation de calibration de caméra à partir d’une seule image avec un contenu générique. Ces trois sujets seront abordés avec une perspective axée sur les données. Chacun de ces axes comporte des analyses de performance approfondies et, malgré la réputation d’opacité des algorithmes d’apprentissage machine profonds, nous proposons des études sur les indices visuels captés par nos méthodes.Understanding images is needed for a plethora of tasks, from compositing to image relighting, including 3D object reconstruction. These tasks allow artists to realize masterpieces or help operators to safely make decisions based on visual stimuli. For many of these tasks, the physical and geometric models that the scientific community has developed give rise to ill-posed problems with several solutions, only one of which is generally reasonable. To resolve these indeterminations, the reasoning about the visual and semantic context of a scene is usually relayed to an artist or an expert who uses his experience to carry out his work. This is because humans are able to reason globally on the scene in order to obtain plausible and appreciable results. Would it be possible to model this experience from visual data and partly or totally automate tasks? This is the topic of this thesis: modeling priors using deep machine learning to solve typically ill-posed problems. More specifically, we will cover three research axes: 1) surface reconstruction using photometric cues, 2) outdoor illumination estimation from a single image and 3) camera calibration estimation from a single image with generic content. These three topics will be addressed from a data-driven perspective. Each of these axes includes in-depth performance analyses and, despite the reputation of opacity of deep machine learning algorithms, we offer studies on the visual cues captured by our methods.
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Polthier, Konrad. "Geometric a priori estimates for hyperbolic minimal surfaces." Bonn : [s.n.], 1994. http://catalog.hathitrust.org/api/volumes/oclc/31760536.html.
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Chebbi, Mohamed Ali. "Similarity learning for large scale dense image matching." Electronic Thesis or Diss., Université Gustave Eiffel, 2024. http://www.theses.fr/2024UEFL2030.
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La thèse porte sur l’amélioration de la qualité des modèles numériques d'élévation (MNE) à partir d’imagerie aérienne et satellitaire. Notre démarche repose sur l’appariement dense d’images combinant la mesure de ressemblance et la régularisation semi-globale. Cependant, elle prévoit des corrélateurs neuronaux à la place des mesures de ressemblance classiques. Malgré les efforts de recherche considérables entrepris au cours des vingt dernières années, les mesures de ressemblance classiques (NCC, Census, etc...) sont généralement limitées surtout face aux zones d’images homogènes, proches des occlusions, ombragées et en présence de surfaces ayant des propriétés de réflectance non lambertienne. Alors que ces approches, fortement dépendantes de la notion de voisinage local, perdent de distinctivité en élargissant le contexte et face à ces scénarios difficiles, les architectures de réseaux neuronaux profonds offrent des capacités d’apprentissage étendues et peuvent appréhender des notions de similarité plus complexes capables ainsi de résoudre ces scénarios d’appariement complexes. Ce travail présente des architectures neuronales et des méthodes basées sur l’apprentissage profond pour l’appariement multi-images en photogrammétrie aérienne et satellitaire. Notre approche vise à apprendre des similarités transférables à l’ensemble des géométries de reconstruction (épipolaire, native et terrain) en œuvrant en accord avec l’a priori de nature géométrique des images. Tout d’abord, la fonction de similarité est apprise sur des paires d’images épipolaires. Ensuite, les similarités apprises sont transformées pour résoudre le problème de correspondance multi-vues sur la base de recalages épipolaires ou homographiques adaptés.Notre approche se démarque du paradigme de correspondance classique qui compense les imperfections des appariements par voisinage local avec des contraintes de surface semi-globales. Plus précisément, nos réseaux neuronaux apprennent de manière contrastive des scores de similarité globaux, expressifs et pixellaires par le biais d’architectures à large champ récepteur. Notre pipeline multi-vues ne nécessite pas de réapprentissage supplémentaire sur des jeux de données dédiés et exploite des géométries de transfert comme moyens pour calculer des descripteurs orientés robustes en géométrie native. Ces derniers sont ré-échantillonnés à chaque plan hypothétique pour évaluer les similarités le long de l’intervalle de profondeur. Contrairement à la fusion a posteriori des cartes de profondeur, notre stratégie multi-vues adopte un schéma de fusion a priori pondérant les similarités apprises par paires pour remplir puis régulariser la structure de coût. Nous établissons un équilibre de performances entre l’apprentissage profond de la similarité et la régression de bout en bout pour la mise en correspondance épipolaire et démontrons que nos modèles produisent des descripteurs généralisables pour la reconstruction de surfaces 3D multi-vues omni-scènes. En tirant parti des pipelines de correspondance multi-résolution hiérarchiques, nos corrélateurs neuronaux peuvent être facilement combinés avec des mesures de similarité classiques pour améliorer la précision des MNE. Les pipelines proposés sont implémentés dans MicMac, un logiciel photogrammétrique gratuit et open sourceDense image matching is a long standing ill-posed problem. Despite the extensive research efforts undertaken in the last twenty years, the state-of-the-art handcrafted algorithms perform poorly on featureless areas, in presence of occlusions, shadows and on non-lambertian surfaces. This is due to lack of distinctiveness of the handcrafted similarity metrics in such challenging scenarios. On the other hand, deep learning based approaches to image matching are able to learn highly non-linear similarity functions thus provide an interesting path to addressing such complex matching scenarios.In this research, we present deep learning based architectures and methods for stereo and multi-view dense image matching tailored to aerial and satellite photogrammetry. The proposed approach is driven by two key ideas. First, our goal is to develop a matching network that is as generic as possible to different sensors and acquisition scenarios. Secondly, we argue that known geometrical relationships between images can alleviate the learning phase and should be leveraged in the process. As a result, our matching pipeline follows the known two step pipeline where we first compute deep similarities between pixel correspondences, followed by depth regularization. This separation ensures “generality” or “transferability” to different scenes and acquisitions. Furthermore, our similarity functions are learnt on epipolar rectified image pairs, and to exploit the learnt embeddings in a general n-view matching problem, geometry priors are mobilized. In other words, we transform embeddings learnt on pairs of images to multi-view embeddings through a priori knowledge about the relative camera poses. This allows us to capitalize on the vast stereo matching benchmarks existing in the literature while extending the approach to multi-view scenarios. Finally, we tackle the insufficient distinctiveness of the state-of-the-art patch-based features/similarities by feeding the network with large images thus adding more context, and by proposing an adapted sample mining scheme. We establish a middle-ground between state-of-the-art similarity learning and end-to-end regression models for stereo matching and demonstrate that our models yield generalizable representations in multiple view 3D surface reconstruction from aerial and satellite acquisitions. The proposed pipelines are implemented in MicMac, a free, open-source photogrammetric software
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Teixeira, Daniel Nascimento. "Uma técnica de decomposição a priori para geração paralela de malhas bidimensionais." reponame:Repositório Institucional da UFC, 2014. http://www.repositorio.ufc.br/handle/riufc/13352.
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TEIXEIRA, D. N. Uma técnica de decomposição a priori para geração paralela de malhas bidimensionais. 2014. 95 f. Dissertação (Mestrado em Ciência da Computação) - Centro de Ciências, Universidade Federal do Ceará, Fortaleza, 2014.Submitted by Daniel Eduardo Alencar da Silva (dealencar.silva@gmail.com) on 2015-01-23T18:25:13Z No. of bitstreams: 1 2014_dis_dnteixeira.pdf: 17919971 bytes, checksum: 092ad12b33cf64a31552e6a839a5a5bc (MD5)
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This work describes a technique of two-dimensional domain decomposition for parallel mesh generation. This technique works for both distributed and shared memory and has the freedom to use any data structure that manages rectangular regions parallel to the axes to decompose the domain given as input, such as a quaternary tree (quadtree) or a binary space decomposition (bsp), for example. Any process of mesh generation that respects the prerequisites established can be used in the subdomains created, for instance, Delaunay or Advancing Front, among others. This technique is called a priori because the mesh on the interface of the subdomains is generated prior to the their internal meshes. The load estimation for each sub-domain in this work is performed with the aid of a refined quadtree, whose level of refinement guides the creation of edges that are defined from the bounderies of only inner cells. This way of estimate load produces results that accurately represent the number of elements to be generated in each subdomain. That contributes to a good partitioning of the domain, making the mesh generation in parallel be significantly faster than the serial generation. Furthermore, the quality of the generated mesh in parallel is qualitatively equivalent to that generated serially within acceptable limits.
Este trabalho descreve uma técnica de decomposição de domínios bidimensionais para geração em paralelo de malhas. Esta técnica funciona tanto para memória distribuída quanto compartilhada, além de permitir que se utilize qualquer estrutura de dados que gere regiões quadrangulares paralelas aos eixos para decompor o domínio dado como entrada. Pode se utilizar por exemplo, uma árvore quaternária (quadtree) ou uma partição binária do espaço (bsp). Além disso, qualquer processo de geração de malha que respeite os pré-requisitos estabelecidos pode ser empregado nos subdomínios criados, como as técnicas de Delaunay ou Avanço de Fronteira, dentre outras. A técnica proposta é dita a priori porque a malha de interface entre os subdomínios é gerada antes das suas malhas internas. A estimativa de carga de processamento associada a cada subdomínio é feita nesse trabalho com a ajuda de uma quadtree refinada, cujo nível de refinamento orienta a criação das arestas que são definidas a partir da discretização das fronteiras das células internas. Essa maneira de estimar carga produz resultados que representam, com boa precisão, o número de elementos a serem gerados em cada subdomínio. Isso contribui para um bom particionamento do domínio, fazendo com que a geração de malha em paralelo seja significativamente mais rápida do que a geração serial. Além disso, a qualidade da malha gerada em paralelo é qualitativamente equivalente àquela gerada serialmente, dentro de limites aceitáveis.
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Teixeira, Daniel Nascimento. "Uma tÃcnica de decomposiÃÃo a priori para geraÃÃo paralela de malhas bidimensionais." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12186.
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CoordenaÃÃo de AperfeiÃoamento de NÃvel SuperiorEste trabalho descreve uma tÃcnica de decomposiÃÃo de domÃnios bidimensionais para geraÃÃo em paralelo de malhas. Esta tÃcnica funciona tanto para memÃria distribuÃda quanto compartilhada, alÃm de permitir que se utilize qualquer estrutura de dados que gere regiÃes quadrangulares paralelas aos eixos para decompor o domÃnio dado como entrada. Pode se utilizar por exemplo, uma Ãrvore quaternÃria (quadtree) ou uma partiÃÃo binÃria do espaÃo (bsp). AlÃm disso, qualquer processo de geraÃÃo de malha que respeite os prÃ-requisitos estabelecidos pode ser empregado nos subdomÃnios criados, como as tÃcnicas de Delaunay ou AvanÃo de Fronteira, dentre outras. A tÃcnica proposta à dita a priori porque a malha de interface entre os subdomÃnios à gerada antes das suas malhas internas. A estimativa de carga de processamento associada a cada subdomÃnio à feita nesse trabalho com a ajuda de uma quadtree refinada, cujo nÃvel de refinamento orienta a criaÃÃo das arestas que sÃo definidas a partir da discretizaÃÃo das fronteiras das cÃlulas internas. Essa maneira de estimar carga produz resultados que representam, com boa precisÃo, o nÃmero de elementos a serem gerados em cada subdomÃnio. Isso contribui para um bom particionamento do domÃnio, fazendo com que a geraÃÃo de malha em paralelo seja significativamente mais rÃpida do que a geraÃÃo serial. AlÃm disso, a qualidade da malha gerada em paralelo à qualitativamente equivalente Ãquela gerada serialmente, dentro de limites aceitÃveis.
This work describes a technique of two-dimensional domain decomposition for parallel mesh generation. This technique works for both distributed and shared memory and has the freedom to use any data structure that manages rectangular regions parallel to the axes to decompose the domain given as input, such as a quaternary tree (quadtree) or a binary space decomposition (bsp), for example. Any process of mesh generation that respects the prerequisites established can be used in the subdomains created, for instance, Delaunay or Advancing Front, among others. This technique is called a priori because the mesh on the interface of the subdomains is generated prior to the their internal meshes. The load estimation for each sub-domain in this work is performed with the aid of a refined quadtree, whose level of refinement guides the creation of edges that are defined from the bounderies of only inner cells. This way of estimate load produces results that accurately represent the number of elements to be generated in each subdomain. That contributes to a good partitioning of the domain, making the mesh generation in parallel be significantly faster than the serial generation. Furthermore, the quality of the generated mesh in parallel is qualitatively equivalent to that generated serially within acceptable limits.
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Hassan, Sahar. "Intégration de connaissances anatomiques a priori dans des modèles géométriques." Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00607260.
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L'imagerie médicale est une ressource de données principale pour différents types d'applications. Bien que les images concrétisent beaucoup d'informations sur le cas étudié, toutes les connaissances a priori du médecin restent implicites. Elles jouent cependant un rôle très important dans l'interprétation et l'utilisation des images médicales. Dans cette thèse, des connaissances anatomiques a priori sont intégrées dans deux applications médicales. Nous proposons d'abord une chaîne de traitement automatique qui détecte, quantifie et localise des anévrismes dans un arbre vasculaire segmenté. Des lignes de centre des vaisseaux sont extraites et permettent la détection et la quantification automatique des anévrismes. Pour les localiser, une mise en correspondance est faite entre l'arbre vasculaire du patient et un arbre vasculaire sain. Les connaissances a priori sont fournies sous la forme d'un graphe. Dans le contexte de l'identification des sous-parties d'un organe représenté sous forme de maillage, nous proposons l'utilisation d'une ontologie anatomique, que nous enrichissons avec toutes les informations nécessaires pour accomplir la tâche de segmentation de maillages. Nous proposons ensuite un nouvel algorithme pour cette tâche, qui profite de toutes les connaissances a priori disponibles dans l'ontologie.
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Miller-Cotto, Dana. "The role of prior knowledge, executive function, and perceived cognitive load on the effectiveness of faded worked examples in geometry." Diss., Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/439545.
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Educational PsychologyPh.D.
Mathematics remains a subject many students fail to become competent in by the time they graduate from high school. Most students often require one on one, individualized tutoring to help them reach competence. That remains a challenge since most classrooms are understaffed and underfunded, frequently having only one teacher in a overpopulated classroom. One strategy that has been used to alleviate some of this over reliance on the teacher has been faded worked examples, or fading. Fading is the successive removal of the last steps in a series of problems until the student is solving problems completely on their own. The current study aimed to determine whether fading improves learning, and for whom. The goal was to compare fading with business as usual (control), worked examples with self-explanations, and fading with self-explanations. Specifically, I was interested in the following research questions: (1) Do the three experimental conditions differ in promoting posttest scores on surface area and volume? (2) Do the three experimental conditions differ in promoting conceptual knowledge and procedural knowledge of surface area and volume at posttest? and (3) When interaction terms are created between student profiles and conditions within regression analyses, which profiles explain significant variance in posttest scores? Repeated measures analysis of variance, principle axis factor analysis, and simple linear regressions were used to examine the differences between conditions at posttest, to create propensity scores, and to determine whether there were any interactions between propensity scores and conditions. Results indicated a significant effect of fading on posttest scores. A regression with propensity factors indicated that the fading conditions appeared to benefit low propensity students moreso than high propensity students. Findings are discussed in terms of educational implications and future research that can complement these findings to contribute to future research.
Temple University--Theses
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Gonçalves, Junior Eduardo Manuel. "Aspectos computacionais na geometria da espiral de Teodoro." Universidade Federal da Paraíba, 2015. http://tede.biblioteca.ufpb.br:8080/handle/tede/7647.
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The present work is a study of Teodoro spiral, for the geometric aspects of the curve. At rst, the construction of Teodoro spiral in two and three dimensions is made. And through the softwares, GeoGebra and wxMaxima were developed respectively, the geometric constructions and the necessary calculations. With the possession of the spiral of concatenation, observe the pattern of behavior of growth and position, the collared peccary in the n - th triangle. Going through measurements of Teodoro spiral with other spirals such as the Archimedean, we come to denote behavior patterns in expanding spiral. The following is an arithmetic study on the spiral obtained by the length of the branches of the same, both perfect and imperfect hits with square also spaced apart relationship between them allows us to observe numbers as the . The distribution of prime numbers is seen as the nal part of this study, where you see speculatively allowing the formation of new curves on the spiral, as parabolas.
O presente trabalho faz um estudo da espiral de Teodoro, no tocante aos aspectos geométricos da curva. De início, é feita a construção da espiral de Teodoro em duas e três dimensões. E por meio dos softwares, GeoGebra e wxMaxima, foram desenvolvidas respectivamente, as construções geométricas e os cálculos necessários. Com a posse da concatenação da espiral, observa-se o comportamento do padrão de crescimento e posição, do cateto no enésimo triângulo. Passando por aferições da espiral de Teodoro com outras espirais, como por exemplo a arquimediana, chega-se a denotar padrões de comportamento na expansão da espiral. A seguir, é mostrado um estudo aritmético na espiral, obtido através do comprimento dos ramos da mesma, que tanto atinge quadrados perfeitos e imperfeitos como também a relação de afastamento entre eles nos permite observar números como o . A distribuição dos números primos é vista como parte fi nal desse estudo, onde se vê de forma especulativa, possibilitando a formação de novas curvas sobre a espiral, como parábolas.
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Bernardini, Geferson. "Uma atividade didática envolvendo área e volume do cilindro e de prismas." Universidade Federal de São Carlos, 2014. https://repositorio.ufscar.br/handle/ufscar/5965.
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Previous issue date: 2014-04-15Financiadora de Estudos e Projetos
This paper presents a didactic proposal for Spatial Geometry classes in High School. We were taken to create this proposal from our experience as a teacher, when we observed that the study of this content requires experimentation and contextualization activities. The study of the Spatial Geometry is of great importance in High School. It contributes to the development of the capacity of abstraction, solving practical problems of everyday life and helps to acquire skills to estimate and compare results, recognize properties of geometric shapes, calculate areas, volume and working with different units of measure. Our work uses as motivation the problem of constructing a silo for grain storage, for this it is necessary to compare the volumes of the prisms with triangular, square and hexagonal base and of the cylinder without the cover, height and total area of the fixed surface to choose the format representing the highest volume. Our work is not intended to define or obtain formulas to calculate areas and volumes. The main focus of this work is to develop the ability to manipulate these formulas and other knowledge, such as solving quadratic equation, using the Pythagorean theorem, and correctly use the calculator to solve a practical problem. This activity has been applied to three classes of Second Grade High School students in a State School of São Paulo in Agudos town. For this purpose two classes of 100 minutes were used. The pupils enjoyed the activity that was carried out in groups of three and the lesson was without complications. This is a didactic sequence that does not require many resources and may be useful for teachers who want to work the theme in context. Our proposal adopts suggestions from the National Curricular Parameters (NCP) and we believe that can be used by fellow teachers, to which our product is available.
Este trabalho apresenta uma proposta didática para aulas de Geometria Espacial no Ensino Médio. Fomos levados a criar essa proposta a partir de nossa experiência como professor, quando observamos que o estudo desse conteúdo necessita de atividades de experimentação e contextualização. O estudo da Geometria Espacial é de grande importância no Ensino Médio. Contribui para o desenvolvimento da capacidade de abstração, resolução de problemas práticos do quotidiano, e ajuda a adquirir habilidades como estimar e comparar resultados, reconhecer propriedades das formas geométricas, calcular áreas, volumes e trabalhar com diferentes unidades de medida. Nosso trabalho usa como motivação o problema de construir um silo para armazenamento de grãos, para isso é preciso comparar os volumes dos prismas de base triangular, quadrada, hexagonal e do cilindro, sem a tampa, altura e área total da superfície fixa para escolher o formato que apresente o maior volume. Nosso trabalho não tem o objetivo de definir ou obter fórmulas para calcular áreas e volumes. O foco principal deste trabalho é desenvolver a capacidade de manipular tais fórmulas e outros conhecimentos, como por exemplo, resolver equações do segundo grau, utilizar o teorema de Pitágoras e utilizar corretamente a calculadora para resolver um problema prático. Esta atividade foi aplicada em três turmas da segunda série do Ensino Médio de uma escola da Rede Estadual de Ensino de São Paulo em Agudos. Para isso foram utilizadas duas aulas de 100 minutos. Os alunos gostaram da atividade que foi realizada em grupos de três e a aula transcorreu sem complicações. Trata-se de uma sequência didática que não requer muitos recursos e pode ser útil para os professores que pretendam trabalhar o tema de maneira contextualizada. Nossa proposta adota sugestões dos Parâmetros Curriculares Nacionais (PCN) e acreditamos que pode ser utilizada por colegas professores, aos quais nosso produto está disponível.
Books on the topic "Geometry priors"
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Boothroyd, Jennifer. Rectangular prism. Minneapolis, MN: LernerClassroom, 2008.
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Hanson, Anders. What in the world is a prism? Edina, Minn: ABDO Pub. Company, 2008.
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illustrator, Mitter Kathy, ed. Prisms. Minneapolis: Magic Wagon, 2012.
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Bremen, Kunsthalle. Szenen aus dem alten Japan: Japanische Farbholzschnitte aus eigenem Besitz. Bremen: Kunsthalle Bremen, 1990.
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Bremen, Kunsthalle. Szenen aus dem alten Japan: Japanische Farbholzschnitte. Heidelberg: Edition Braus, 1993.
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Shparlinski, Igor E., and David R. Kohel. Frobenius distributions: Lang-Trotter and Sato-Tate conjectures : Winter School on Frobenius Distributions on Curves, February 17-21, 2014 [and] Workshop on Frobenius Distributions on Curves, February 24-28, 2014, Centre International de Rencontres Mathematiques, Marseille, France. Providence, Rhode Island: American Mathematical Society, 2016.
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1973-, Tobias Uwe, Görner Veit, Schrader Kristin, Takis George Frederick, and Kestner-Gesellschaft, eds. Gert & Uwe Tobias. Köln: Snoeck, 2009.
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artist, Tobias Uwe 1973, and Sprengel Museum Hannover, eds. Gert & Uwe Tobias: Collagen. Dortmund: Verlag Kettler, 2016.
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1973-, Tobias Uwe, Gronert Stefan, Löbke Matthia, Städtisches Kunstmuseum Bonn, and Kunstverein Heilbronn, eds. Gert & Uwe Tobias. Köln: Snoeck, 2008.
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1973-, Tobias Uwe, and Nöllenheidt Sarah, eds. Gert & Uwe Tobias. Köln: Snoeck, 2007.
Find full textBook chapters on the topic "Geometry priors"
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Li, Chaojian, Bichen Wu, Albert Pumarola, Peizhao Zhang, Yingyan Lin, and Peter Vajda. "INGeo: Accelerating Instant Neural Scene Reconstruction with Noisy Geometry Priors." In Lecture Notes in Computer Science, 686–94. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25066-8_40.
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Fu, Xiao, Wei Yin, Mu Hu, Kaixuan Wang, Yuexin Ma, Ping Tan, Shaojie Shen, Dahua Lin, and Xiaoxiao Long. "GeoWizard: Unleashing the Diffusion Priors for 3D Geometry Estimation from a Single Image." In Lecture Notes in Computer Science, 241–58. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-72670-5_14.
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Hacyan, Shahen. "Geometry a Priori." In The Frontiers Collection, 111–17. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-21254-3_13.
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Koch-Medina, Pablo, and Cosimo Munari. "Random Variables: Topology and Geometry." In Market-Consistent Prices, 59–82. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39724-1_3.
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Blackwell, Kenneth, Andrew Brink, Nicholas Griffin, Richard A. Rempel, and John G. Slater. "The À Priori in Geometry [1896]." In The Collected Papers of Bertrand Russell, Volume 1, 289–304. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003555698-58.
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Lötjönen, J., I. E. Magnin, L. Reinhardt, J. Nenonen, and T. Katila. "Automatic Reconstruction of 3D Geometry Using Projections and a Geometric Prior Model." In Medical Image Computing and Computer-Assisted Intervention – MICCAI’99, 192–201. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/10704282_21.
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Riklin-Raviv, Tammy, Nahum Kiryati, and Nir Sochen. "Unlevel-Sets: Geometry and Prior-Based Segmentation." In Lecture Notes in Computer Science, 50–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24673-2_5.
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Böhm, Janko, Wolfram Decker, Claus Fieker, Santiago Laplagne, and Gerhard Pfister. "Bad Primes in Computational Algebraic Geometry." In Mathematical Software – ICMS 2016, 93–101. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42432-3_12.
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Harney, Hanns L. "Beyond Form Invariance: The Geometric Prior." In Bayesian Inference, 71–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-06006-3_9.
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Lorenzen, Paul. "Geometry as the Measure-Theoretic a Priori of Physics." In Constructivism and Science, 127–44. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-0959-5_7.
Full textConference papers on the topic "Geometry priors"
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Wang, Qingfeng, Lingyu Liang, and Shuangping Huang. "Document Image Dewarping Guided by 3D Geometry and Layout Priors." In 2024 IEEE International Conference on Multimedia and Expo (ICME), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/icme57554.2024.10687513.
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Perry, Travis, and Andrew Gallaher. "Automated Layout with a Python Integrated NDARC Environment." In Vertical Flight Society 74th Annual Forum & Technology Display, 1–11. The Vertical Flight Society, 2018. http://dx.doi.org/10.4050/f-0074-2018-12723.
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Geometric layout of an aircraft concept is a fundamental aspect of the design process and can often be a primary driver for design choices, and trade space decisions. Most commonly, geometry is either estimated analytically by performance and sizing tools, from in-production aircraft data, or modeled using Computer Aided Design (CAD). Analytic geometry estimates are often not precise, requiring CAD to refine these estimates. Modeling an aircraft design to the fidelity needed to refine these geometric estimates can be a time consuming process. Furthermore, the initial layout design iterations are primarily used to refine prior estimates rather than address layout design choices. There is a need to accomplish these high level layout tasks in a timely manner; allowing for broad trade space analysis, and relying on CAD later in the design process for more detailed geometric layout. This paper will cover the development of the Automated Layout with a Python Integrated NDARC Environment (ALPINE), a Python Application Programming Interface (API) based geometry tool which leverages outputs from NASA Design and Analysis of Rotorcraft (NDARC) and the geometry software OpenVSP to expedite high level layout processes. ALPINE is an object oriented API tool that streamlines the initial conceptual layout process. This is accomplished through mapping NDARC geometry parameters to custom components generated in OpenVSP, and using algorithms native to OpenVSP. Through the use of this tool, the time needed for initial geometric layout is reduced significantly, potential design challenges can be highlighted without a detailed CAD model, geometry can be integrated within closed loop design optimization problems, and analytic geometry estimates from performance sizing codes can be refined and correlated to 3D model-based analyses.
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Dong, Yuan, Qi Zuo, Xiaodong Gu, Weihao Yuan, Zhengyi Zhao, Zilong Dong, Liefeng Bo, and Qixing Huang. "GPLD3D: Latent Diffusion of 3D Shape Generative Models by Enforcing Geometric and Physical Priors." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 56–66. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.00014.
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Ji, Shihao, Kun Jiang, Peng Wang, and Mingyi He. "RE-Net: Road Extraction from Remote Sensing Images with Deep Learning and Geometric Priors." In 2024 IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), 1–6. IEEE, 2024. http://dx.doi.org/10.1109/iciea61579.2024.10664713.
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Myers, Adele, and Nina Miolane. "On Accuracy and Speed of Geodesic Regression: Do Geometric Priors Improve Learning on Small Datasets?" In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2714–22. IEEE, 2024. http://dx.doi.org/10.1109/cvprw63382.2024.00277.
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Knoll, Jonathan, and Jeffrey Nissen. "Integration of 3D Scan Data into the Finite Element Analysis Workflow for Simulation of Rotorcraft Components." In Vertical Flight Society 71st Annual Forum & Technology Display, 1–14. The Vertical Flight Society, 2015. http://dx.doi.org/10.4050/f-0071-2015-10264.
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A process for integrating 3D scan data into the finite element analysis (FEA) workflow is presented. The process was developed to utilize CAD and/or scan-based geometry to create a 3D Finite Element model for structural analysis. Three significant phases of the process include surface acquisition, geometric refinement, and FEA evaluation. The scan-based process provides a cost effective method to capture the surface geometry of physical components and permits a digital representation of the article to be created for analysis purposes. It is shown that the role of alignment, deviation checking, and prior analysis are significant factors in efficiently developing models for FEA. The application of scan-based FEA was highly effective in simulating component repairs, weldments, and predicting mechanical test behavior. Results from these applications were substantiated by digital image correlation and strain gauge data, showing excellent correlation between 3-10%. When comparing scan-based FEA results it was found that accounting for paint thickness can have a significant effect on the accuracy of the results. With a successful scan-based FEA approach developed, numerous applications of the process resulted in reduced scrap rate, supported safety of flight testing, and ensured continued on-time delivery of aircraft.
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Johari, Mohammad Mahdi, Yann Lepoittevin, and Francois Fleuret. "GeoNeRF: Generalizing NeRF with Geometry Priors." In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2022. http://dx.doi.org/10.1109/cvpr52688.2022.01782.
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Rombach, Robin, Patrick Esser, and Bjorn Ommer. "Geometry-Free View Synthesis: Transformers and no 3D Priors." In 2021 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2021. http://dx.doi.org/10.1109/iccv48922.2021.01409.
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Chen, Huiqin, Emanuel Aldea, Sylvie Le Hegarat-Mascle, and Vincent Despiegel. "Use of Scene Geometry Priors for Data Association in Egocentric Views." In 2020 8th International Workshop on Biometrics and Forensics (IWBF). IEEE, 2020. http://dx.doi.org/10.1109/iwbf49977.2020.9107955.
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Shahsavari, Sina, Jiawen Chen, and Piya Pal. "Exploring the Geometry of Generative Priors with Applications in Cellular MRI." In 2022 56th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2022. http://dx.doi.org/10.1109/ieeeconf56349.2022.10052006.
Full textReports on the topic "Geometry priors"
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Moorehead, Stewart. Unsettled Topics in Obstacle Detection for Autonomous Agricultural Vehicles. SAE International, December 2021. http://dx.doi.org/10.4271/epr2021029.
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Agricultural vehicles often drive along the same terrain day after day or year after year. Yet, they still must detect if a moveable object, such as another vehicle or an animal, happens to be on their path or if environmental conditions have caused muddy spots or washouts. Obstacle detection is one of the major missing pieces that can remove humans from highly automated agricultural machines today and enable the autonomous vehicles of the future. Unsettled Topics in Obstacle Detection for Autonomous Agricultural Vehicles examines the challenges of environmental object detection and collision prevention, including air obscurants, holes and soft spots, prior maps, vehicle geometry, standards, and close contact with large objects.
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Zevotek, Robin, and Steve Kerber. Fire Service Summary Report: Study of the Effectiveness of Fire Service Positive Pressure Ventilation During Fire Attack in Single Family Homes Incorporating Modern Construction Practices. UL Firefighter Safety Research Institute, May 2016. http://dx.doi.org/10.54206/102376/ncck4947.
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There is a continued tragic loss of firefighter and civilian lives, as shown by fire statistics. One significant contributing factor is the lack of understanding of fire behavior in residential structures resulting from the use of ventilation as a firefighter practice on the fire ground. The changing dynamics of residential fires as a result of the changes in home construction materials, contents, size and geometry over the past 30 years compounds our lack of understanding of the effects of ventilation on fire behavior. Positive Pressure Ventilation (PPV) fans were introduced as a technology to increase firefighter safety by controlling the ventilation. However, adequate scientific data is not available for PPV to be used without increasing the risk to firefighters. This fire research report details the experimental data from cold flow experiments, fuel load characterization experiments and full scale fire experiments. During the project it was identified that the positive pressure attack (PPA) and positive pressure ventilation (PPV) were often used interchangeably. For the purpose of this report they have been defined as PPA for when the fan is utilized prior to fire control and PPV for when the fan is used post fire control. The information from the full scale tests was reviewed with assistance from our technical panel of fire service experts to develop tactical considerations for the use of PPV fans in residential single family structures.
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Zevotek, Robin, and Steve Kerber. Study of the Effectiveness of Fire Service Positive Pressure Ventilation During Fire Attack in Single Family Homes Incorporating Modern Construction Practices. UL Firefighter Safety Research Institute, May 2016. http://dx.doi.org/10.54206/102376/gsph6169.
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There is a continued tragic loss of firefighter and civilian lives, as shown by fire statistics. One significant contributing factor is the lack of understanding of fire behavior in residential structures resulting from the use of ventilation as a firefighter practice on the fire ground. The changing dynamics of residential fires as a result of the changes in home construction materials, contents, size and geometry over the past 30 years compounds our lack of understanding of the effects of ventilation on fire behavior. Positive Pressure Ventilation (PPV) fans were introduced as a technology to increase firefighter safety by controlling the ventilation. However, adequate scientific data is not available for PPV to be used without increasing the risk to firefighters. This fire research report details the experimental data from cold flow experiments, fuel load characterization experiments and full scale fire experiments. During the project it was identified that the positive pressure attack (PPA) and positive pressure ventilation (PPV) were often used interchangeably. For the purpose of this report they have been defined as PPA for when the fan is utilized prior to fire control and PPV for when the fan is used post fire control. The information from the full scale tests was reviewed with assistance from our technical panel of fire service experts to develop tactical considerations for the use of PPV fans in residential single family structures.
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Näslund-Hadley, Emma, Haydée Alonzo, Neulin Villanueva, Ricardo Gideon, and Yvonne Flowers. The Effects of the COVID-19 Pandemic on Education Outcomes in Belize. Inter-American Development Bank, April 2023. http://dx.doi.org/10.18235/0004836.
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The COVID-19 pandemic brought school systems to a halt across the globe. In Belize, remote learning was challenging owing to limited access to educational technologies and lack of familiarity with remote learning among teachers. This study draws on national standardized exams and specific achievement testing to assess pandemic-related learning losses at the primary education level. Based on administrative data, the study also analyzes changes in student enrollment, dropout rates, and grade repetition at the primary and secondary levels. We find that school closures resulted in significant learning losses in English language and mathematics at the end of primary education. Matching international trends, the largest losses occurred in mathematics. Among the strands of mathematics content, the one showing the most dramatic loss is number sense in primary schools and geometry in secondary schools; the achievement level in both dropped by around 55 percent. Also, in line with international trends, average student repetition and dropout rates surged at the secondary level after prolonged school closures. The largest increase in dropout and repetition levels were found in urban secondary schools: the average dropout rate increased by 51 percent in the 2020/21 school year, compared with the average rate in the year prior to the start of the pandemic, while the repetition rate increased from 6.7 percent in the 2019/20 school year to 11.6 percent in the 2021/22 school year.
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Beshouri. PR-309-04200-R01 Modeling Methodology for Parametric Emissions Monitoring System for Combustion Turbines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), March 2005. http://dx.doi.org/10.55274/r0010731.
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Prior attempts to develop a generic Parametric Emissions Monitoring methodology for combustion turbines, particularly low emissions units, have failed due either to the reduction of a complex problem to too few degrees of freedom or the brute force reliance on regression analysis. Field test data collected by the research team clearly illustrated that a successful PEMS model will need to incorporate multiple zones to account for pilot fuel versus pre-mixed combustion, and changes in air/fuel ratio at the flame front. The information reported herein shows that, ideally, the PEMS model should rely on speed, fuel flow, compressor discharge pressure and temperature, and ambient conditions as the inputs. The model can utilize (combustion turbine) turbine discharge temperatures as cross checks and/or for tuning. Make and model specific geometric characteristics should include compressor air flow versus speed, air splits between the combustor and the cooling air, and the fuel splits between diffusion and premixed. Finally, the model should be able to accommodate fuel that varies in composition based on provided gas speciation.
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Kyriakides. L51559 Factors Affecting Pipe Collapse Phase II. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 1988. http://dx.doi.org/10.55274/r0010129.
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Offshore pipelines installed in moderate to deep water depths (1,500 ft. and beyond) must, by necessity, be designed to withstand ambient external pressure. Improper design can lead to catastrophic collapse of large sections of the structure. During the installation process the line can experience significant bending and tension loads in addition to external pressure. These additional loads can significantly reduce the collapse pressure of the pipe. Special purpose combined loading test facilities were designed and built in which pressures equivalent to 10,000 ft. and beyond were simulated. The test facilities were used to establish load interaction collapse envelopes for the two types of combined loading mentioned. Bending/pressure collapse envelopes were generated for tubes with diameter to thickness ratios of 34.7, 24.5, 18.2 and 17.3. Tension/pressure collapse envelopes were generated for tubes with diameter to thickness ratios of 38.3, 24.5, 18.2 and 12.2. The geometric imperfections and material parameters were recorded for all test specimen's prior to collapse. Under bending/pressure loading the tube response, the critical collapse loads and the nature of the instabilities observed were found to depend on the loading path. Collapse was found to be relatively insensitive to the history for tension/pressure loading.
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Yoosef-Ghodsi, Ozkan, and Bandstra. PR-244-114501-R01 Review of Compressive Strain Capacity Assessment Methods Final Report. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), October 2013. http://dx.doi.org/10.55274/r0010402.
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Buried pipelines subjected to non-continuous ground movement such as frost heave, thaw settlement, slope instability and seismic movement experience high compressive strains that can cause local buckling (or wrinkling), in which the pipe wall buckles like a thin cylindrical shell in axial compression. In a strain-based design and assessment framework, excessive local buckling deformation that may cause loss of serviceability, or even pressure containment in some cases, is managed by limiting the strain demand below the strain limit. The determination of compressive strain limit is typically performed by full-scale structural testing or nonlinear finite element analysis that takes into account material and geometric non-linearity associated with the inelastic buckling of cylindrical shells. Before performing testing and numerical analysis (or when such options do not exist), empirical equations are used to estimate the strain limit. In this report a number of representative equations were evaluated by comparing strain limit predictions to full-scale test results. Work prior to this study has identified the importance of key variables that have the greatest impact on the local buckling behaviour. Examples of these variables include the diameter-to-thickness (D/t) ratio, internal pressure and shape of the stress strain curve. The evaluation focused on how existing equations address these key variables, and the performance with respect to key variables and in different ranges.
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Briggs, Nicholas E., Robert Bailey Bond, and Jerome F. Hajjar. Cyclic Behavior of Steel Headed Stud Anchors in Concrete-filled Steel Deck Diaphragms through Push-out Tests. Northeastern University. Department of Civil and Environmental Engineering., February 2023. http://dx.doi.org/10.17760/d20476962.
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Earthquake disasters in the United States account for $6.1 billion of economic losses each year, much of which is directly linked to infrastructure damage. These natural disasters are unpredictable and represent one of the most difficult design problems in regard to constructing resilient infrastructure. Structural floor and roof diaphragms act as the horizontal portion of the lateral force resisting system (LFRS), distributing the seismically derived inertial loads out from the heavy concrete slabs to the vertical LFRS. Composite concrete-filled steel deck floor and roof diaphragms are ubiquitously used in commercial construction worldwide due to the ease of construction and cost-effective use of structural material. This report presents a series of composite steel deck diaphragm Push-out tests at full scale that explore the effect that cyclic loading has on the strength of steel headed stud anchors. The effect that cyclic loading has on structural performance is explored across the variation of material and geometric parameters in the Push-out specimens, such as concrete density, steel headed stud anchor placement and grouping, steel deck orientation, and edge conditions. As compared to prior tests in the literature, the push-out tests conducted in this work have an extended specimen length that includes four rows of studs along the length rather than the typical two rows of studs, and an ability to impose cyclic loading. This provides novel insight into force flows in the specimens, failure mechanisms, and load distribution between studs and stud groups.
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Leis and Brust. L51665 Hydrotest Strategies for Gas Transmission Pipelines Based on Ductile-Flaw-Growth Considerations. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), July 1992. http://dx.doi.org/10.55274/r0010296.
Full textAbstract:
Historically safe operation of thousands of miles of gas- transmission pipeline underscores the merits of hydrotesting. The hydrotest is applied to remove defects, which might exist in the line and could be critical in subsequent service. The hydrotest involves a proof pressurization that is designed to remove defects that could otherwise become critical in service by failing these defects during the time the line is held at the over-pressure. Water is used as the pressurization media to avoid the potential for running fracture, which is possible in cases where defects become critical during the test when using more compressible media (e.g., gases). Hydrotesting is not the only means to ensure defects that could become critical in subsequent service are identified and removed from a line. For example, inline inspection (ILI) procedures are available that permit the identification of specific types of defects, such as corrosion. But because not all lines can be inspected with ILI tools and the need to find types of defects that are not currently detected by inline procedures, hydrotesting remains the method of choice in the USA for natural gas transmission lines. The objective of this study was to determine the growth of various flaw sizes as a result of having been subjected to combinations of test pressures and hold times and to assess the subsequent serviceability of pipelines containing those flaws in gas-transmission service. The purpose of the flaw-growth calculations is to define hydrotest procedures for gas-transmission pipelines that remove flaws that could become critical in service while minimizing the growth of any remaining flaws. This report is the fourth in a series of topical reports dealing with quasi-static ductile flaw growth in pipelines, such as can occur in a hydrotest. Prior reports presented relevant material properties, the theoretical analysis, and the model development and validation. This report presents the results and analysis of an extensive parametric study of ductile flaw growth as a function of maximum test pressure, hold time, flaw geometry, and strength and toughness of the pipe steel representative of submerged-arc welded pipe in grades from X52 through X70 with a yield-to-ultimate ratio less than 0.90.
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Perdigão, Rui A. P., and Julia Hall. Spatiotemporal Causality and Predictability Beyond Recurrence Collapse in Complex Coevolutionary Systems. Meteoceanics, November 2020. http://dx.doi.org/10.46337/201111.
Full textAbstract:
Causality and Predictability of Complex Systems pose fundamental challenges even under well-defined structural stochastic-dynamic conditions where the laws of motion and system symmetries are known. However, the edifice of complexity can be profoundly transformed by structural-functional coevolution and non-recurrent elusive mechanisms changing the very same invariants of motion that had been taken for granted. This leads to recurrence collapse and memory loss, precluding the ability of traditional stochastic-dynamic and information-theoretic metrics to provide reliable information about the non-recurrent emergence of fundamental new properties absent from the a priori kinematic geometric and statistical features. Unveiling causal mechanisms and eliciting system dynamic predictability under such challenging conditions is not only a fundamental problem in mathematical and statistical physics, but also one of critical importance to dynamic modelling, risk assessment and decision support e.g. regarding non-recurrent critical transitions and extreme events. In order to address these challenges, generalized metrics in non-ergodic information physics are hereby introduced for unveiling elusive dynamics, causality and predictability of complex dynamical systems undergoing far-from-equilibrium structural-functional coevolution. With these methodological developments at hand, hidden dynamic information is hereby brought out and explicitly quantified even beyond post-critical regime collapse, long after statistical information is lost. The added causal insights and operational predictive value are further highlighted by evaluating the new information metrics among statistically independent variables, where traditional techniques therefore find no information links. Notwithstanding the factorability of the distributions associated to the aforementioned independent variables, synergistic and redundant information are found to emerge from microphysical, event-scale codependencies in far-from-equilibrium nonlinear statistical mechanics. The findings are illustrated to shed light onto fundamental causal mechanisms and unveil elusive dynamic predictability of non-recurrent critical transitions and extreme events across multiscale hydro-climatic problems.