Zobrazeno 1 - 10
of 32 607
pro vyhledávání: '"Guérin, A"'
Publikováno v:
Journ{\'e}es de la SF2A, Jun 2024, Marseille, France
We present a preliminary laboratory test of a setup designed to measure Hanbury Brown and Twiss-type intensity correlations from a chaotic light source using five spectral channels simultaneously. After averaging the zero-delay correlation peaks from
Externí odkaz:
http://arxiv.org/abs/2411.08417
Studies conducted on the experimental site of Lavalette (IRSTEA Montpellier) have shown variability in the observed agricultural yield, either attributable to spatial or temporal heterogeneities in water and nitrogen supply or to gradients of soil pr
Externí odkaz:
http://arxiv.org/abs/2411.11877
Recent advances in machine learning and hardware have produced embedded devices capable of performing real-time object detection with commendable accuracy. We consider a scenario in which embedded devices rely on an onboard object detector, but have
Externí odkaz:
http://arxiv.org/abs/2410.18919
From the observation of a diffusion path $(X_t)_{t\in [0,T]}$ on a compact connected $d$-dimensional manifold $M$ without boundary, we consider the problem of estimating the stationary measure $\mu$ of the process. Wang and Zhu (2023) showed that for
Externí odkaz:
http://arxiv.org/abs/2410.11777
This work tackles the challenge of efficiently selecting high-performance pre-trained vision backbones for specific target tasks. Although exhaustive search within a finite set of backbones can solve this problem, it becomes impractical for large dat
Externí odkaz:
http://arxiv.org/abs/2410.08592
Effective models to describe the dynamics of an open cavity have been extensively discussed in the literature. In many of these models the cavity leakage to the outside is treated as a loss introduced phenomenologically. In contrast to these, we focu
Externí odkaz:
http://arxiv.org/abs/2410.06379
Active perception enables robots to dynamically gather information by adjusting their viewpoints, a crucial capability for interacting with complex, partially observable environments. In this paper, we present AP-VLM, a novel framework that combines
Externí odkaz:
http://arxiv.org/abs/2409.17641
We investigate a human-like interpretable model of video understanding. Humans recognise complex activities in video by recognising critical spatio-temporal relations among explicitly recognised objects and parts, for example, an object entering the
Externí odkaz:
http://arxiv.org/abs/2409.13091
When the memory parameter of the elephant random walk is above a critical threshold, the process becomes superdiffusive and, once suitably normalised, converges to a non-Gaussian random variable. In a recent paper by the three first authors, it was s
Externí odkaz:
http://arxiv.org/abs/2409.06836
Detecting actions in videos, particularly within cluttered scenes, poses significant challenges due to the limitations of 2D frame analysis from a camera perspective. Unlike human vision, which benefits from 3D understanding, recognizing actions in s
Externí odkaz:
http://arxiv.org/abs/2408.15679