21 to 30 of 68 Results
Höke, Benjamin; Gauß, Florian; Peek, Christina; Stelzner, Jörg, 2020, "Lauchheim II.3. Katalog der Gräber 601–900 [Supplement]", https://doi.org/10.11588/data/NRHERZ, heiDATA, V1
Mit rund 1300 Gräbern aus dem Zeitraum vom späten 5. bis zum späten 7. Jahrhundert ist das Gräberfeld von Lauchheim "Wasserfurche" (Ostalbkreis) bis heute der größte bekannte merowingerzeitliche Bestattungsplatz Süddeutschlands. In den Jahren 1986 bis 1996 wurde das fast vollstän... |
Isenbeck-Schröter, Margot; Ritter, Simon Michael, 2020, "Datensatz zum Verbundprojekt GeoSpeicher.bw: Geothermische Speicherung in Baden-Württemberg", https://doi.org/10.11588/data/GLQLSH, heiDATA, V1, UNF:6:yuWXTkgSzO/g/grDjaWLDg== [fileUNF]
Datensatz zu Abschlussbericht des Verbundprojekts GeoSpeicher.bw: Geothermische Speicherung in Baden-Württemberg Teilprojekt Heidelberg: Einfluss der Einspeicherung von Wärme im oberflächennahen Aquifer auf die Hydrogeochemie des Aquifers (Geospeicher.HD) |
Sep 18, 2020
This Dataverse contains research data of the research group Hydrogeochemistry and Hydrogeology of the Institute of Earth sciences. The research group Hydrogeochemistry and Hydrogeology of the Institute of Earth sciences Heidelberg is mainly focused on studies on the groundwater q... |
Sep 14, 2020 - AWI Experimental Economics
Apesteguia, Jose; Oechssler, Jörg; Weidenholzer, Simon, 2020, "Copy Trading [Dataset]", https://doi.org/10.11588/data/PAMQ0B, heiDATA, V1, UNF:6:GrGXrQgTcdgZl5admIPidA== [fileUNF]
Copy trading allows traders in social networks to receive information on the success of other agents in financial markets and to directly copy their trades. Internet platforms like eToro, ZuluTrade, and Tradeo have attracted millions of users in recent years. The present paper st... |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Differentiable RANSAC (DSAC) for Visual Re-Localization [Data]", https://doi.org/10.11588/data/3JVZSH, heiDATA, V1
Pre-trained models of our camera re-localization method for the MSR 7Scenes dataset. For more information, also see the code documentation: https://github.com/cvlab-dresden/DSAC |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "DSAC++ Visual Camera Re-Localization [Data]", https://doi.org/10.11588/data/EGCMUU, heiDATA, V1
Supplementary training data for visual camera re-localization, particularly rendered depth maps to be used in combination with the Cambridge Landmarks dataset. We also provide pre-trained models of our method for the MSR 7Scenes dataset and the Cambridge Landmarks dataset. For mo... |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "6D Object Pose Estimation using 3D Object Coordinates [Data]", https://doi.org/10.11588/data/V4MUMX, heiDATA, V1
Supplementary training data and binaries for 6D object pose estimation, particularly a dataset of 20 objects under various lighting conditions with RGB-D images, ground truth poses and segmentation as well as 3D models. Additionally, a collection of RGB-D images showing office ba... |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Neural-Guided RANSAC for Estimating Epipolar Geometry [Data]", https://doi.org/10.11588/data/PCGYET, heiDATA, V1
Pre-computed sparse feature correspondences for pairs of images (outdoor and indoor) to reproduce the experiments described in our paper, particularly to train and evaluate NG-RANSAC. For more information, also see the code documentation: https://github.com/vislearn/ngransac |
Sep 7, 2020 - IWR Visual Learning Lab
Brachmann, Eric, 2020, "Expert Sample Consensus (ESAC) for Visual Re-Localization [Data]", https://doi.org/10.11588/data/GSJE9D, heiDATA, V1
Supplementary training data for visual camera re-localization, particularly pre-computed scene coordinates to the MSR 7Scenes dataset and the Standford 12Scenes dataset. We also provide pre-trained models of our method for the 7Scenes, 12Scenes, Dubrovnik and Aachen (day) dataset... |
Leuschner, Florian, 2020, "(MI)MI Model", https://doi.org/10.11588/data/Y6Y7P0, heiDATA, V1, UNF:6:+YH2Zdq/RGjq2VJMW9SMQQ== [fileUNF]
Source data for 'A minimal-invasive approach for standardized induction of myocardial infarction in mice'. |
