Zobrazeno 1 - 10
of 20 461
pro vyhledávání: '"BUCHHOLZ P"'
Monocular geometric scene understanding combines panoptic segmentation and self-supervised depth estimation, focusing on real-time application in autonomous vehicles. We introduce MGNiceNet, a unified approach that uses a linked kernel formulation fo
Externí odkaz:
http://arxiv.org/abs/2411.11466
Depth estimation is an essential task toward full scene understanding since it allows the projection of rich semantic information captured by cameras into 3D space. While the field has gained much attention recently, datasets for depth estimation lac
Externí odkaz:
http://arxiv.org/abs/2411.11455
Autor:
Brady, Jack, von Kügelgen, Julius, Lachapelle, Sébastien, Buchholz, Simon, Kipf, Thomas, Brendel, Wieland
Learning disentangled representations of concepts and re-composing them in unseen ways is crucial for generalizing to out-of-domain situations. However, the underlying properties of concepts that enable such disentanglement and compositional generali
Externí odkaz:
http://arxiv.org/abs/2411.07784
Autor:
Buchholz, Detlev, Yngvason, Jakob
Some advantages of the algebraic approach to many body physics, based on resolvent algebras, are illustrated by the simple example of non-interacting bosons which are confined in compact regions with soft boundaries. It is shown that the dynamics of
Externí odkaz:
http://arxiv.org/abs/2411.04737
Autor:
Buchholz, Benjamin
Plasma current instabilities can destabilize the plasma discharge and cool the plasma rapidly. In such $\textit{disruptions}$ or in the start-up phase of the reactor, inductive electric fields are generated which accelerate electrons to relativistic
Externí odkaz:
http://arxiv.org/abs/2410.19474
Conflicting sensor measurements pose a huge problem for the environment representation of an autonomous robot. Therefore, in this paper, we address the self-assessment of an evidential grid map in which data from conflicting LiDAR sensor measurements
Externí odkaz:
http://arxiv.org/abs/2409.20286
We propose an approach to assess the synchronization of rigidly mounted sensors based on their rotational motion. Using function similarity measures combined with a sliding window approach, our approach is capable of estimating time-varying time offs
Externí odkaz:
http://arxiv.org/abs/2409.20266
Autor:
D'Silva, Nicholas, Shahi, Toran, Husveg, Øyvind Timian Dokk, Sanjeeve, Adith, Buchholz, Erik, Kanhere, Salil S.
Once analysed, location trajectories can provide valuable insights beneficial to various applications. However, such data is also highly sensitive, rendering them susceptible to privacy risks in the event of mismanagement, for example, revealing an i
Externí odkaz:
http://arxiv.org/abs/2409.14645
We introduce STAResNet, a ResNet architecture in Spacetime Algebra (STA) to solve Maxwell's partial differential equations (PDEs). Recently, networks in Geometric Algebra (GA) have been demonstrated to be an asset for truly geometric machine learning
Externí odkaz:
http://arxiv.org/abs/2408.13619
Location trajectories provide valuable insights for applications from urban planning to pandemic control. However, mobility data can also reveal sensitive information about individuals, such as political opinions, religious beliefs, or sexual orienta
Externí odkaz:
http://arxiv.org/abs/2407.16938