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124 results for “Mur”
Renovation du Mur - Abbaye de Grestain
 Située à quelques kilomètres de Honfleur, l'abbaye Notre-Dame de Grestain à Fatouville-Grestain (Eure) est un haut lieu du moyen-âge anglo-normand. Depuis 2011, elle propose, saison après saison, un riche programme culturel fait de visites commentées, de conférences, de concerts, de théâtre et d'expositions L'ancienne abbaye de Grestain est ouverte gratuitement au public toute l'année. Horaires des visites, de 10h à 18h. Source: Objaverse 1.0 / Sketchfab
Wall and flowers - Mur et fleurs
Old stone wall with flower. Photogrammetry scan (74x24mp), 2x4k textures Source: Objaverse 1.0 / Sketchfab
Multi-Dimensional Simulation of the Volumetric Database by Video - Mapping Technology of Sea surface temperature remotley sensed (Algerian basin) ( SST : 2003 - 2007 - 2015 - 2019 ) (L4, MUR,GHRSST)
<p><span>Marine data, which are volumetric data, contain a variety of information about a water body (e.g., seawater temperature, salinity, density, and current) (Feng Zhang et all.,2019),due to its large scale, random variation and multi-resolution in nature, are hard to be visualized and analyzed (Jerry, 2001; Claes, 2004). Moreover, people can not observe the internal characteristics and phenomena of the ocean directly and comprehensively. ‘Digital Ocean’, which emerged after ‘Digital Earth’, focuses on analyzing ocean phenomena and serves for ocean applications. ‘Digital Earth’ is an information system including massive, multi-resolution, multi-temporal marine databases and analysis algorithms (Shi and Lei, 2011). Nowadays, constructing an ocean model and visualizing volumetric data have become some of the most important and critical research topics of ‘Digital Ocean’. The study of marine volumetric data visualization can be valuable in many other research areas (Coelho et al., 2004).</span></p> <p><span>Volume visualization, one of the most important fields of scientific visualization, is the process of generating meaningful and visual information on a two-dimensional image plane from three dimensional datasets. It has been increasingly important in geographical information systems to improve the ocean modeling (Gonzato and Saec, 2000; Djurcilov et al., 2002)</span> </p> <p><strong><span>REF :</span></strong></p> <p><span>Feng Zhang, Ruichen Mao, Zhenhong Du, Renyi Liu,Spatial and temporal processes visualization for marine environmental data using particle system,Computers & Geosciences, Volume 127,2019,Pages 53-64,ISSN 0098-3004,https://doi.org/10.1016/j.cageo.2019.02.012.</span></p> <p><span>Jerry, T., 2001. Simulating ocean water. ACM SIGGRAPH (Special Interest Group on Computer Graphics) 2001 Course Notes, Los Angeles, <a href="http://home1.get.net/tssndrf/"><span>http://home1.get.net/tssndrf/</span></a>.</span></p> <p><span>Claes, J., 2004. Real time water rendering. Master thesis. Department of Computer Science, Lund University</span></p> <p><span>Shi, S. X., and Lei, B., 2011. Theory and Practice on China Digital Ocean. Ocean Press, Beijing, 80-100.</span></p> <p><span><span>Coelho, A., Nascimento, M., Bentes, C., de Castro, M. C. S.,and Farias, R., 2004. Parallel volume rendering for ocean visualization in a cluster of PCS. In: <em>Proceeding of VI Brazilian</em> <em>Symposium on Geoinformatics</em>, Campos do Jordão, São Paulo, Brazil, 22- 24.</span></span></p> <p><span>Gonzato, J. C., and Saec, B. L., 2000. On modeling and rendering ocean scenes. <em>Journal of Visualisation and Computer</em> <em>Animation</em>, <strong>11 </strong>(1): 27-37.</span></p> <p><span>Djurcilov, S., Kim, K., Lermusiaux, P. F. J., and Pang, A., 2002.Visualizing scalar volumetric data with uncertainty. <em>Computers</em> <em>and Graphics</em>, <strong>2 </strong>(26): 239-248.</span></p>
Graz. - Mur Schloßberg.
<u>Source</u>: Europeana <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1653128135.5046.jpg">https://4dcity.org/imgupload/1653128135.5046.jpg</a> <br><u>Original Image URL</u>: <a href="https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fgams.uni-graz.at%2Fiiif%2Fo%3Agm.2889%252FRECTO%2Ffull%2Ffull%2F0%2Fdefault.jpg&type=IMAGE">https://api.europeana.eu/thumbnail/v2/url.json?uri=https%3A%2F%2Fgams.uni-graz.at%2Fiiif%2Fo%3Agm.2889%252FRECTO%2Ffull%2Ffull%2F0%2Fdefault.jpg&type=IMAGE</a> <br><br><u>Image-Metadata:</u><br>Filename: 1653128135.5046.jpg<br>Image Dimensions: 400x266<br>Megapixels: 0.11 MP<br>Filesize: 43.72 KB<br>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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International Brain Laboratory public data
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OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.