Zobrazeno 1 - 10
of 177
pro vyhledávání: '"Koch, Steffen"'
The visualization and interactive exploration of geo-referenced networks poses challenges if the network's nodes are not evenly distributed. Our approach proposes new ways of realizing animated transitions for exploring such networks from an ego-pers
Externí odkaz:
http://arxiv.org/abs/2406.11493
Autor:
Beck, Samuel, Doerr, Nina, Kurzhals, Kuno, Riedlinger, Alexander, Schmierer, Fabian, Sedlmair, Michael, Koch, Steffen
Sports visualization has developed into an active research field over the last decades. Many approaches focus on analyzing movement data recorded from unstructured situations, such as soccer. For the analysis of choreographed activities like formatio
Externí odkaz:
http://arxiv.org/abs/2404.04100
Autor:
Chen, Changjian, Chen, Jiashu, Yang, Weikai, Wang, Haoze, Knittel, Johannes, Zhao, Xibin, Koch, Steffen, Ertl, Thomas, Liu, Shixia
Temporal action localization aims to identify the boundaries and categories of actions in videos, such as scoring a goal in a football match. Single-frame supervision has emerged as a labor-efficient way to train action localizers as it requires only
Externí odkaz:
http://arxiv.org/abs/2312.05178
Autor:
Franke, Max, Koch, Steffen
Publikováno v:
In Proceedings of 2023 IEEE Visualization and Visual Analytics (VIS), pp. 191-195
Periodically occurring accumulations of events or measured values are present in many time-dependent datasets and can be of interest for analyses. The frequency of such periodic behavior is often not known in advance, making it difficult to detect an
Externí odkaz:
http://arxiv.org/abs/2307.15483
Publikováno v:
Engineering Computations, 2024, Vol. 41, Issue 6, pp. 1424-1440.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/EC-12-2023-0952
Autor:
Knittel, Johannes, Koch, Steffen, Tang, Tan, Chen, Wei, Wu, Yingcai, Liu, Shixia, Ertl, Thomas
Breaking news and first-hand reports often trend on social media platforms before traditional news outlets cover them. The real-time analysis of posts on such platforms can reveal valuable and timely insights for journalists, politicians, business an
Externí odkaz:
http://arxiv.org/abs/2108.03052
Spherical k-Means is frequently used to cluster document collections because it performs reasonably well in many settings and is computationally efficient. However, the time complexity increases linearly with the number of clusters k, which limits th
Externí odkaz:
http://arxiv.org/abs/2108.00895
Autor:
Chen, Ping, Van Loon, Luc R., Koch, Steffen, Alt-Epping, Peter, Reich, Tobias, Churakov, Sergey V.
Publikováno v:
In Applied Clay Science April 2024 251
Keyphrase extraction methods can provide insights into large collections of documents such as social media posts. Existing methods, however, are less suited for the real-time analysis of streaming data, because they are computationally too expensive
Externí odkaz:
http://arxiv.org/abs/2102.05700
Investigating relationships between variables in multi-dimensional data sets is a common task for data analysts and engineers. More specifically, it is often valuable to understand which ranges of which input variables lead to particular values of a
Externí odkaz:
http://arxiv.org/abs/2009.05502