A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

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Low-light photography produces images with low signal-to-noise ratios due to limited photons. In such conditions, common approximations like the Gaussian noise model fall short, and many denoising techniques fail to remove noise effectively. Although deep- ...

This paper presents a combination of three computational methods in a hybrid approach designed to model the radiation of antennas within arbitrarily shaped capsules implanted in a host body. A surface method of moments is employed to represent the radiatio ...

Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variation linked to health and disease1,2. However, existing data-sharing regulations limit the scope of such collaborations3. Although crypt ...

There is a bias in the inference pipeline of most diffusion models. This bias arises from a signal leak whose distribution deviates from the noise distribution, creating a discrepancy between training and inference processes. We demonstrate that this signa ...

We prove global in time well-posedness for perturbations of the 2D stochastic Navier-Stokes equations partial derivative( t)u + u center dot del u = Delta u - del p + sigma + xi, u(0, center dot ) = u(0),div (u) = 0, driven by additive space-time white noi ...

With a growing emphasis on indoor air quality (IAQ) in educational environments, CO2 monitoring in classrooms has become commonplace. CO2 data can be used to estimate outdoor air change rate (ACH) based on the mass balance principle, which can be further l ...

Remote photoplethysmography (rPPG) using camera-based imaging has shown excellent potential recently in vital signs monitoring due to its contactless nature. However, the optimum filter selection for pre-processing rPPG data in signal conditioning is still ...

Indoor environmental quality (IEQ) has a profound impact on occupant health, comfort, and performance. Various methods are employed to collect feedback from building users, ranging from conventional questionnaires, increasingly utilized physiological monit ...

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 paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

Ion transport through biological and solid-state nanochannels is known to be a highly noisy process. The power spectrum of current fluctuations is empirically known to scale like the inverse of frequency, following the long-standing yet poorly understood H ...

The remarkable ability of deep learning (DL) models to approximate high-dimensional functions from samples has sparked a revolution across numerous scientific and industrial domains that cannot be overemphasized. In sensitive applications, the good perform ...

Within the context of contemporary machine learning problems, efficiency of optimization process depends on the properties of the model and the nature of the data available, which poses a significant problem as the complexity of either increases ad infinit ...

We consider fluid flows, governed by the Navier-Stokes equations, subject to a steady symmetry-breaking bifurcation and forced by a weak noise acting on a slow timescale. By generalizing the multiple-scale weakly nonlinear expansion technique employed in t ...

Reinterpretable cameras are defined by their post-processing capabilities that exceed traditional imaging. We present "SoDaCam" that provides reinterpretable cameras at the granularity of photons, from photon-cubes acquired by single-photon devices. Photon ...

Proton magnetic resonance spectroscopic imaging (1H-MRSI) is a powerful tool that enables the multidimensional non-invasive mapping of the neurochemical profile at high resolution over the entire brain. The constant demand for higher spatial resolution in ...

A multi-agent system consists of a collection of decision-making or learning agents subjected to streaming observations from some real-world phenomenon. The goal of the system is to solve some global learning or optimization problem in a distributed or dec ...

Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...

Decentralized learning is appealing as it enables the scalable usage of large amounts of distributed data and resources (without resorting to any central entity), while promoting privacy since every user minimizes the direct exposure of their data. Yet, wi ...

A Versatile Noise Performance Metric for Electrical Impedance Tomography Algorithms

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Dark Noise Diffusion: Noise Synthesis for Low-Light Image Denoising

A Hybrid Method for Optimizing Radiation of Implantable Antennas in Diverse Scenarios

Secure and federated genome-wide association studies for biobank-scale datasets

Exploiting the Signal-Leak Bias in Diffusion Models

Global existence for perturbations of the 2D stochastic Navier-Stokes equations with space-time white noise

Estimating Air Change Rate in Mechanically Ventilated Classrooms Using a Single CO2 Sensor and Automated Data Segmentation

Optimal digital filter selection for remote photoplethysmography (rPPG) signal conditioning

Exploring indoor environmental perception through questionnaires, physiological monitoring, and facial expression recognition

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

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation

Spectral Estimators for High-Dimensional Matrix Inference

Disentangling 1/f noise from confined ion dynamics

Towards Trustworthy Deep Learning for Image Reconstruction

Universal and adaptive methods for robust stochastic optimization

Noise-induced transitions past the onset of a steady symmetry-breaking bifurcation: The case of the sudden expansion

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Noise-reduction techniques for 1H-FID-MRSI at 14.1 T: Monte Carlo validation and in vivo application

Multi-agent Learning with Privacy Guarantees

Functional data analysis with rough sample paths?

The Privacy Power of Correlated Noise in Decentralized Learning