Novel Concepts and Recent Progress in Distributed Optical Fiber Sensing

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Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems". The corresponding scripts can be accessed on GitHub (https://github.com/axgoujon/convex_ridge_regularizers). The data is organized as follows: - ct_data_sets.tar.gz: contains prepr ...

Air traffic noise emissions are responsible for a significant part of the overall environmental noise, especially in the vicinity of airports. Exposure to environmental noise is known to negatively impact health and to be associated with cardiovascular dis ...

This paper introduces Wireless IoT-based Noise Cancellation (WINC) which defines a framework for leveraging a wireless network of IoT microphones to enhance active noise cancellation in noise-canceling headphones. The IoT microphones forward ambient noise ...

This dataset contains aerosol optical absorption coefficients at seven different wavelengths (babs(λ)), averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed ...

Controlling audible sound requires inherently broadband and subwavelength acoustic solutions, which are to date, crucially missing. This includes current noise absorption methods, such as porous materials or acoustic resonators, which are typically ineffic ...

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

This dataset contains equivalent black carbon (eBC) concentrations, averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed in the Swiss container on the D-dec ...

A Mach-Zehnder Interferometer (MZI) based optical fibre sensing technique, developed and patented by EPFL, is an efficient and economical way to detect hotspots in High Temperature Superconductor (HTS) applications. Due to the MZI sensitivity being a compo ...

The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

Image noise can often be accurately fitted to a Poisson-Gaussian distribution. However, estimating the distribution parameters from a noisy image only is a challenging task. Here, we study the case when paired noisy and noise-free samples are accessible. N ...

High-energy hadron colliders are designed to generate particle collisions within specialized detectors. A higher number of collisions is achieved with high-quality beams of low transverse emittances, meaning a small transverse cross-section, and high inten ...

Laser phase noise remains a limiting factor in many experimental settings, including metrology, time-keeping, as well as quantum optics. Hitherto this issue was addressed at low frequencies ranging from well below 1 Hz to maximally 100 kHz. However, a wide ...

Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as phys ...

Intrinsic neutron noise experiments offer a non-invasive manner to measure the prompt decay constant or reactivity of fissile systems. Using the fluctuations in the density of fission chains, one can infer the kinetics parameters via correlation analysis s ...

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

Understanding the implicit bias of training algorithms is of crucial importance in order to explain the success of overparametrised neural networks. In this paper, we study the dynamics of stochastic gradient descent over diagonal linear networks through i ...

Class A shot-noise limited operation is achieved in an electrically pumped vertical external cavity surface emitting laser (VECSEL), opening the way for integration of such peculiar noiseless laser oscillation in applications where low power consumption an ...

In 2016, our research team proposed in an issue of Nature Communications1 the use of multidimensional signal processing, especially image denoising techniques, to improve the signal-to-noise ratio (SNR) of distributed optical ﬁbre sensors. The beneﬁts of t ...

Following the performance breakthrough of denoising networks, improvements have come chiefly through novel architecture designs and increased depth. While novel denoising networks were designed for real images coming from different distributions, or for sp ...

A major challenge to the scalability of cryogenic computing platforms is the heat load associated with the growing number of electrical cable connections between the superconducting circuitry and the room-temperature environment. Compared with electrical c ...

Novel Concepts and Recent Progress in Distributed Optical Fiber Sensing

Chattez avec Graph Search

Data for: "A Neural-Network-Based Convex Regularizer for Inverse Problems"

Robust tunable acoustic impedance control on electroacoustic resonators for aircraft noise reduction

WINC: A Wireless IoT Network for Multi-Noise Source Cancellation

Aerosol optical absorption coefficients at seven wavelengths in 10 min resolution measured in the Swiss container during MOSAiC 2019/2020

Ultrabroadband sound control with deep-subwavelength plasmacoustic metalayers

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

Equivalent black carbon concentration in 10 minutes time resolution, measured in the Swiss container during MOSAiC 2019/2020

Optical fibre based quench detection in HTS applications using machine learning classifiers

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

PoGaIN: Poisson-Gaussian Image Noise Modeling From Paired Samples

Transverse Noise, Decoherence, and Landau Damping in High-Energy Hadron Colliders

High-frequency broadband laser phase noise cancellation using a delay line

PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain

Towards the Validation of Noise Experiments in the CROCUS Reactor Using the TRIPOLI-4 Monte Carlo Code in Analog Mode

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks

Implicit Bias of SGD for Diagonal Linear Networks: a Provable Benefit of Stochasticity

Electrically pumped shot-noise limited class A VECSEL at telecom wavelength

Evaluating measurement uncertainty in Brillouin distributed optical fibre sensors using image denoising

Deep Gaussian denoiser epistemic uncertainty and decoupled dual-attention fusion

A cryogenic electro-optic interconnect for superconducting devices