Tootfinder

Environment Reconstruction based on Multi-User Selection and Multi-Modal Fusion in ISAC
Bo Lin, Chuanbin Zhao, Feifei Gao, Geoffrey Ye Li
https://arxiv.org/abs/2403.17810

Environment Reconstruction based on Multi-User Selection and Multi-Modal Fusion in ISAC
Integrated sensing and communications (ISAC) has been deemed as a key technology for the sixth generation (6G) wireless communications systems. In this paper, we explore the inherent clustered nature of wireless users and design a multi-user based environment reconstruction scheme. Specifically, we first select users based on the estimation precision of channel's multipath, including the line-of-sight (LOS) and the non-line-of-sight (NLOS) paths, to enhance the accuracy of environment reconstru…

Nachdem sie monatelang eine globale Policy vorschoben, weshalb #Tesla in #Schweden keinen Tarifvertrag unterzeichnen könnte, sagen sie nun, dass sie eigentlich das Mandat hätten, nur nicht wollen. Persönlich finde ich das äußerst seltsam und wünsche der

Tesla Sveriges helomvändning: Har mandat att teckna kollektivavtal – men vill inte
I snart fem månader har IF Metall strejkat mot Tesla eftersom elbilsjätten vägrar teckna kollektivavtal. Efter en lång tid av stiltje bryter nu Tesla tystnaden – med ett helt nytt budskap.

Concentration estimates for SPDEs driven by fractional Brownian motion
Nils Berglund (Neamtu), Alexandra Blessing (Neamtu)
https://arxiv.org/abs/2404.16485

Concentration estimates for SPDEs driven by fractional Brownian motion
The main goal of this work is to provide sample-path estimates for the solution of slowly time-dependent SPDEs perturbed by a cylindrical fractional Brownian motion. Our strategy is similar to the approach by Berglund and Nader for space-time white noise. However, the setting of fractional Brownian motion does not allow us to use any martingale methods. Using instead optimal estimates for the probability that the supremum of a Gaussian process exceeds a certain level, we derive concentration es…

Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
Jinhua Liang, Ines Nolasco, Burooj Ghani, Huy Phan, Emmanouil Benetos, Dan Stowell
https://arxiv.org/abs/2403.18638

Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims to train a versatile animal sound detector using only a small set of audio samples. Previous efforts in this area have utilized different architectures and data augmentation techniques to enhance model performance. However, these approaches have not …

Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
Jinhua Liang, Ines Nolasco, Burooj Ghani, Huy Phan, Emmanouil Benetos, Dan Stowell
https://arxiv.org/abs/2403.18638

Mind the Domain Gap: a Systematic Analysis on Bioacoustic Sound Event Detection
Detecting the presence of animal vocalisations in nature is essential to study animal populations and their behaviors. A recent development in the field is the introduction of the task known as few-shot bioacoustic sound event detection, which aims to train a versatile animal sound detector using only a small set of audio samples. Previous efforts in this area have utilized different architectures and data augmentation techniques to enhance model performance. However, these approaches have not …

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https://www.krone.at/3249747