61 to 70 of 1,643 Results
May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 416.6 KB -
MD5: 53e07c85875898048ddc9605ec37a52b
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 245.1 KB -
MD5: 7c5c87f9736bf5f628f46fec3a025ef7
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 411.2 KB -
MD5: dd3170a7e4d9dd626dec049a0e56e4f2
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 220.0 KB -
MD5: 2bd38fd3b633e2b99ec006f005d23344
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Tabular Data - 75.0 KB - 13 Variables, 1143 Observations - UNF:6:E3SROxRmTcGbJ1ofdnmuQQ==
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May 28, 2025 -
Replication data for: Voronoi Cell Interface-Based Parameter Sensitivity Analysis for Labeled Samples
Jupyter Notebook - 9.4 MB -
MD5: b5c33cf21b8296e0db6be85ca86b0027
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May 28, 2025 - PN 6-4
Schäfer, Noel; Künzel, Sebastian; Tilli, Pascal; Munz-Körner, Tanja; Vidyapu, Sandeep; Vu, Ngoc Thang; Weiskopf, Daniel, 2025, "Extended Visual Analysis System for Scene-Graph-Based Visual Question Answering", https://doi.org/10.18419/DARUS-3909, DaRUS, V1
Source code of our extended visual analysis system to explore scene-graph-based visual question answering. This approach is built on top of the state-of-the-art GraphVQA framework which was trained on the GQA dataset. Additionally, it is an improved version of our system that can be found here Instructions on how to use our system can be found in t... |
Unknown - 2.7 MB -
MD5: dcfd845bd702ec32c9a1f535055851d4
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May 21, 2025 - Dissertation Janusch Töpler
Töpler, Janusch, 2025, "Source code for: generating scattering geometrical imperfections", https://doi.org/10.18419/DARUS-5060, DaRUS, V1
This repository contains the python code for the generation of realistically scattering bow and twist imperfections of softwood glulam timber beam-columns. The model was developed in the dissertation of Janusch Töpler. |
Python Source Code - 6.9 KB -
MD5: 8c3ffcbd807c11ce809a4a9fdf2a1311
A python script for generating scattering geometrical imperfections as described in the dissertation of Janusch Töpler. |