Zobrazeno 1 - 10
of 47 696
pro vyhledávání: '"Mathis A"'
Autor:
Philipp Markus, Alperovich Anna, Lisogorov Alexander, Gutt-Will Marielena, Mathis Andrea, Saur Stefan, Raabe Andreas, Mathis-Ullrich Franziska
Publikováno v:
Current Directions in Biomedical Engineering, Vol 8, Iss 1, Pp 30-33 (2022)
Machine learning-based solutions rely heavily on the quality and quantity of the training data. In the medical domain, the main challenge is to acquire rich and diverse annotated datasets for training. We propose to decrease the annotation efforts an
Externí odkaz:
https://doaj.org/article/78bde9aa78b84800b3fd95562013ee8f
Autor:
Philipp Markus, Bacher Neal, Nienhaus Jonas, Hauptmann Lars, Lang Laura, Alperovich Anna, Gutt-Will Marielena, Mathis Andrea, Saur Stefan, Raabe Andreas, Mathis-Ullrich Franziska
Publikováno v:
Current Directions in Biomedical Engineering, Vol 7, Iss 1, Pp 67-71 (2021)
Towards computer-assisted neurosurgery, scene understanding algorithms for microscope video data are required. Previous work utilizes optical flow to extract spatiotemporal context from neurosurgical video sequences. However, to select an appropriate
Externí odkaz:
https://doaj.org/article/7b7301169aba4357b6bcf22a2dd6b583
Autor:
Mathis, Stéphane
Internal gravity waves (hereafter IGWs) are one of the mechanisms that can play a key role to redistribute efficiently angular momentum in stars along their evolution. The study of IGWs is thus of major importance since space-based asteroseismology r
Externí odkaz:
http://arxiv.org/abs/2411.13925
Autor:
Sicca, Vladmir, Xia, Tianxiang, Fédérico, Mathïs, Gorinski, Philip John, Frieder, Simon, Jui, Shangling
We introduce a new symbolic solver for geometry, called Newclid, which is based on AlphaGeometry. Newclid contains a symbolic solver called DDARN (derived from DDAR-Newclid), which is a significant refactoring and upgrade of AlphaGeometry's DDAR symb
Externí odkaz:
http://arxiv.org/abs/2411.11938
Autor:
Mathis, Léo
We study the expected number of solutions of a system of identically distributed exponential sums with centered Gaussian coefficient and arbitrary variance. We use the Adler and Taylor theory of Gaussian random fields to identify a moment map which a
Externí odkaz:
http://arxiv.org/abs/2411.11345
Autor:
Fullana, Tomas, Kulkarni, Yash, Fricke, Mathis, Popinet, Stéphane, Afkhami, Shahriar, Bothe, Dieter, Zaleski, Stéphane
In this work, we revisit the Generalized Navier Boundary condition (GNBC) introduced by Qian et al. in the sharp interface Volume-of-Fluid context. We replace the singular uncompensated Young stress by a smooth function with a characteristic width $\
Externí odkaz:
http://arxiv.org/abs/2411.10762
We consider the problem of text-to-video generation tasks with precise control for various applications such as camera movement control and video-to-video editing. Most methods tacking this problem rely on providing user-defined controls, such as bin
Externí odkaz:
http://arxiv.org/abs/2411.10501
Accurately determining the shape and location of internal structures within deformable objects is crucial for medical tasks that require precise targeting, such as robotic biopsies. We introduce LUDO, a method for accurate low-latency understanding o
Externí odkaz:
http://arxiv.org/abs/2411.08777
Understanding the global organization of complicated and high dimensional data is of primary interest for many branches of applied sciences. It is typically achieved by applying dimensionality reduction techniques mapping the considered data into low
Externí odkaz:
http://arxiv.org/abs/2411.05443
Autor:
Caprais, Mathis, Bergeron, André
In this study, the Method of Characteristics (MOC) for Delayed Neutron Precursors (DNPs) is used to solve the precursors balance equation with turbulent diffusion. The diffusivity of DNPs, significantly higher than molecular diffusivity, emerges in t
Externí odkaz:
http://arxiv.org/abs/2411.03788