Zobrazeno 1 - 10
of 5 911
pro vyhledávání: '"Gossard, A A"'
While table tennis players primarily rely on visual cues, sound provides valuable information. The sound generated when the ball strikes the racket can assist in predicting the ball's trajectory, especially in determining the spin. While professional
Externí odkaz:
http://arxiv.org/abs/2409.11760
Spin plays a pivotal role in ball-based sports. Estimating spin becomes a key skill due to its impact on the ball's trajectory and bouncing behavior. Spin cannot be observed directly, making it inherently challenging to estimate. In table tennis, the
Externí odkaz:
http://arxiv.org/abs/2404.09870
Autor:
Ziegler, Andreas, Vetter, Karl, Gossard, Thomas, Tebbe, Jonas, Otte, Sebastian, Zell, Andreas
Neuromorphic Computing (NC) and Spiking Neural Networks (SNNs) in particular are often viewed as the next generation of Neural Networks (NNs). NC is a novel bio-inspired paradigm for energy efficient neural computation, often relying on SNNs in which
Externí odkaz:
http://arxiv.org/abs/2403.10677
In recent years, robotic table tennis has become a popular research challenge for perception and robot control. Here, we present an improved table tennis robot system with high accuracy vision detection and fast robot reaction. Based on previous work
Externí odkaz:
http://arxiv.org/abs/2310.19062
Accurate calibration is crucial for using multiple cameras to triangulate the position of objects precisely. However, it is also a time-consuming process that needs to be repeated for every displacement of the cameras. The standard approach is to use
Externí odkaz:
http://arxiv.org/abs/2309.12685
Spin plays a considerable role in table tennis, making a shot's trajectory harder to read and predict. However, the spin is challenging to measure because of the ball's high velocity and the magnitude of the spin values. Existing methods either requi
Externí odkaz:
http://arxiv.org/abs/2303.03879
Autor:
de Gournay, Frédéric, Gossard, Alban
In the context of the optimization of Deep Neural Networks, we propose to rescale the learning rate using a new technique of automatic differentiation. This technique relies on the computation of the {\em curvature}, a second order information whose
Externí odkaz:
http://arxiv.org/abs/2210.14520
Publikováno v:
Machine.Learning.for.Biomedical.Imaging. 2 (2023)
Data-driven optimization of sampling patterns in MRI has recently received a significant attention.Following recent observations on the combinatorial number of minimizers in off-the-grid optimization, we propose a framework to globally optimize the s
Externí odkaz:
http://arxiv.org/abs/2209.07170
Event cameras are becoming increasingly popular in robotics and computer vision due to their beneficial properties, e.g., high temporal resolution, high bandwidth, almost no motion blur, and low power consumption. However, these cameras remain expens
Externí odkaz:
http://arxiv.org/abs/2209.04634
A recent trend in the signal/image processing literature is the optimization of Fourier sampling schemes for specific datasets of signals. In this paper, we explain why choosing optimal non Cartesian Fourier sampling patterns is a difficult nonconvex
Externí odkaz:
http://arxiv.org/abs/2207.10323