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pro vyhledávání: '"Rösch, Philipp"'
Current multimodal models leveraging contrastive learning often face limitations in developing fine-grained conceptual understanding. This is due to random negative samples during pretraining, causing almost exclusively very dissimilar concepts to be
Externí odkaz:
http://arxiv.org/abs/2403.02875
Recognising reinforced concrete defects (RCDs) is a crucial element for determining the structural integrity, traffic safety and durability of bridges. However, most of the existing datasets in the RCD domain are derived from a small number of bridge
Externí odkaz:
http://arxiv.org/abs/2309.03763
Reliably identifying reinforced concrete defects (RCDs)plays a crucial role in assessing the structural integrity, traffic safety, and long-term durability of concrete bridges, which represent the most common bridge type worldwide. Nevertheless, avai
Externí odkaz:
http://arxiv.org/abs/2309.00460
Autor:
Rösch, Philipp J., Libovický, Jindřich
In most Vision-Language models (VL), the understanding of the image structure is enabled by injecting the position information (PI) about objects in the image. In our case study of LXMERT, a state-of-the-art VL model, we probe the use of the PI in th
Externí odkaz:
http://arxiv.org/abs/2305.10046
Autor:
Dannecker, Lars, Rösch, Philipp, Fischer, Ulrike, Gaumnitz, Gordon, Lehner, Wolfgang, Hackenbroich, Gregor
Continuous balancing of energy demand and supply is a fundamental prerequisite for the stability of energy grids and requires accurate forecasts of electricity consumption and production at any point in time. Today's Energy Data Management (EDM) syst
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80643
https://tud.qucosa.de/api/qucosa%3A80643/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80643/attachment/ATT-0/
Autor:
Lorenz, Robert, Dannecker, Lars, Rösch, Philipp, Lehner, Wolfgang, Hackenbroich, Gregor, Schlegel, Benjamin
Forecasting is an important data analysis technique and serves as the basis for business planning in many application areas such as energy, sales and traffic management. The currently employed statistical models already provide very accurate predicti
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80441
https://tud.qucosa.de/api/qucosa%3A80441/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80441/attachment/ATT-0/
Forecasting is used as the basis for business planning in many application areas such as energy, sales and traffic management. Time series data used in these areas is often hierarchically organized and thus, aggregated along the hierarchy levels base
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A80366
https://tud.qucosa.de/api/qucosa%3A80366/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A80366/attachment/ATT-0/
Autor:
Rösch, Philipp, Lehner, Wolfgang
The rapid growth of current data warehouse systems makes random sampling a crucial component of modern data management systems. Although there is a large body of work on database sampling, the problem of automatic sample selection remained (almost) u
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A83046
https://tud.qucosa.de/api/qucosa%3A83046/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A83046/attachment/ATT-0/
Autor:
Lehner, Wolfgang, Rösch, Philipp
With the amount of data in current data warehouse databases growing steadily, random sampling is continuously gaining in importance. In particular, interactive analyses of large datasets can greatly benefit from the significantly shorter response tim
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A76731
https://tud.qucosa.de/api/qucosa%3A76731/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A76731/attachment/ATT-0/
Random sampling is a popular technique for providing fast approximate query answers, especially in data warehouse environments. Compared to other types of synopses, random sampling bears the advantage of retaining the dataset’s dimensionality; it a
Externí odkaz:
https://tud.qucosa.de/id/qucosa%3A82224
https://tud.qucosa.de/api/qucosa%3A82224/attachment/ATT-0/
https://tud.qucosa.de/api/qucosa%3A82224/attachment/ATT-0/