Zobrazeno 1 - 10
of 4 361
pro vyhledávání: '"Zöllner, P."'
Autor:
Orf, Stefan, Ochs, Sven, Doll, Jens, Schotschneider, Albert, Heinrich, Marc, Zofka, Marc René, Zöllner, J. Marius
Fault diagnosis is crucial for complex autonomous mobile systems, especially for modern-day autonomous driving (AD). Different actors, numerous use cases, and complex heterogeneous components motivate a fault diagnosis of the system and overall syste
Externí odkaz:
http://arxiv.org/abs/2411.09643
Autor:
Zöllner, Rico, Kämpfer, Burkhard
A core-corona decomposition of compact (neutron) star models is compared to recent NICER data of masses and radii. It is in particular interesting to capture the outlier XTE~J1814-338. Instead of integrating the TOV equations from the center to surfa
Externí odkaz:
http://arxiv.org/abs/2411.08068
Autor:
Ochs, Sven, Yazgan, Melih, Polley, Rupert, Schotschneider, Albert, Orf, Stefan, Uecker, Marc, Zipfl, Maximilian, Burger, Julian, Vivekanandan, Abhishek, Amritzer, Jennifer, Zofka, Marc René, Zöllner, J. Marius
As cities strive to address urban mobility challenges, combining autonomous transportation technologies with intelligent infrastructure presents an opportunity to transform how people move within urban environments. Autonomous shuttles are particular
Externí odkaz:
http://arxiv.org/abs/2410.20989
Autor:
Wilflingseder, Christoph, Aberl, Johannes, Navarette, Enrique Prado, Hesser, Günter, Groiss, Heiko, Liedke, Maciej O., Butterling, Maik, Wagner, Andreas, Hirschmann, Eric, Corley-Wiciak, Cedric, Zoellner, Marvin H., Capellini, Giovanni, Fromherz, Thomas, Brehm, Moritz
Germanium (Ge), the next-in-line group-IV material, bears great potential to add functionality and performance to next-generation nanoelectronics and solid-state quantum transport based on silicon (Si) technology. Here, we investigate the direct epit
Externí odkaz:
http://arxiv.org/abs/2410.03295
Autor:
Uecker, Marc, Zöllner, J. Marius
Recently, LiDAR perception methods for autonomous vehicles, powered by deep neural networks have experienced steep growth in performance on classic benchmarks, such as nuScenes and SemanticKITTI. However, there are still large gaps in performance whe
Externí odkaz:
http://arxiv.org/abs/2409.18592
Autor:
Polley, Nikolai, Pavlitska, Svetlana, Boualili, Yacin, Rohrbeck, Patrick, Stiller, Paul, Bangaru, Ashok Kumar, Zöllner, J. Marius
Effective traffic light detection is a critical component of the perception stack in autonomous vehicles. This work introduces a novel deep-learning detection system while addressing the challenges of previous work. Utilizing a comprehensive dataset
Externí odkaz:
http://arxiv.org/abs/2409.07284
Autor:
Mayr, Martin, Dreier, Marcel, Kordon, Florian, Seuret, Mathias, Zöllner, Jochen, Wu, Fei, Maier, Andreas, Christlein, Vincent
The imitation of cursive handwriting is mainly limited to generating handwritten words or lines. Multiple synthetic outputs must be stitched together to create paragraphs or whole pages, whereby consistency and layout information are lost. To close t
Externí odkaz:
http://arxiv.org/abs/2409.00786
Representing diverse and plausible future trajectories of actors is crucial for motion forecasting in autonomous driving. However, efficiently capturing the true trajectory distribution with a compact set is challenging. In this work, we propose a no
Externí odkaz:
http://arxiv.org/abs/2407.20732
In real-world autonomous driving, deep learning models can experience performance degradation due to distributional shifts between the training data and the driving conditions encountered. As is typical in machine learning, it is difficult to acquire
Externí odkaz:
http://arxiv.org/abs/2407.14306
Autor:
Zöllner, Rico, Kämpfer, Burkhard
The holographic Einstein-Maxwell-dilaton model is employed to map state-of-the-art lattice QCD thermodynamics data from the temperature ($T$) axis towards the baryon-chemical potential ($\mu_B$) axis aimed at gaining a warm equation of state (EoS) of
Externí odkaz:
http://arxiv.org/abs/2407.02096