Shot noise influence in reconstructed phase images SNR in digital holographic microscopy

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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 ...

The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. The prevailing challenge in live-cell fluorescence microscopy is capturing intra-cellular dynamics while preservi ...

The aircraft assembly system is highly complex involving different stakeholders from multiple domains. The design of such a system requires comprehensive consideration of various industrial scenarios aiming to optimize key performance indicators. Tradition ...

We describe a novel method to compute the components of dynamo tensors from direct magnetohydrodynamic (MHD) simulations. Our method relies upon an extension and generalization of the standard H & ouml;gbom CLEAN algorithm widely used in radio astronomy to ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

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 ...

Recently, the diffusion moving-average (D-MA) scheme has been proposed as a way to combat noisy links over adaptive networks. However, the current theoretical results focus on networks with mean-square error costs where the optimal local solution agrees wi ...

The manuscript describes the development of a spatial Agent-based Simulation to model the effect of public policies on private houseowner’s decisions concerning their heating system. The methodology utilized comprises of an empirical survey to determine th ...

We report the development of a continuous-wave and pulsed X-band electron spin resonance (ESR) spectrometer for the study of spins on ordered surfaces down to cryogenic temperatures. The spectrometer operates in ultra-high vacuum and utilizes a half-wavele ...

In this article, we consider decentralized optimization problems where agents have individual cost functions to minimize subject to subspace constraints that require the minimizers across the network to lie in low-dimensional subspaces. This constrained fo ...

When spatially shared among multiple tenants, field-programmable gate arrays (FPGAs) are vulnerable to remote power side-channel analysis attacks. Using carefully crafted on-chip voltage sensors, adversaries can extract secrets (e.g., encryption keys or th ...

Cerebrovascular reactivity (CVR), defined as the cerebral blood flow response to a vasoactive stimulus, is an imaging biomarker with demonstrated utility in a range of diseases and in typical development and aging processes. A robust and widely implemented ...

The evolution of the 3D morphology is at the center of many relevant biological processes ranging from cellular differentiation to cancer invasion and metastasis. Microscopy techniques, such as electron microscopy (EM), super-resolution (SR) optical micros ...

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 ...

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 ...

Optical microscopy is an essential tool for biologists, who are often faced with the need to overcome the spatial and temporal resolution limitations of their devices to capture finer details. As upgrading imaging hardware is expensive, computational metho ...

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 ...

A central question of machine learning is how deep nets manage to learn tasks in high dimensions. An appealing hypothesis is that they achieve this feat by building a representation of the data where information irrelevant to the task is lost. For image da ...

A Phase-contrast imaging (PCI) diagnostic provides measurements of line-integrated electron density fluctuations. Localisation along the laser beam path can be achieved with a spatial filter that selects the wave-vector directions of the fluctuations contr ...

Shot noise influence in reconstructed phase images SNR in digital holographic microscopy

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Exploiting the Signal-Leak Bias in Diffusion Models

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

Live-cell imaging powered by computation

An aircraft assembly process formalism and verification method based on semantic modeling and MBSE

Iterative removal of sources to model the turbulent electromotive force

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

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

Diffusion Moving-Average Adaptation Over Networks

Spatial Agent-Based Modelling and Simulation to Evaluate on Public Policies for Energy Transition

A continuous-wave and pulsed X-band electron spin resonance spectrometer operating in ultra-high vacuum for the study of low dimensional spin ensembles

Quantization for Decentralized Learning Under Subspace Constraints

Active Wire Fences for Multitenant FPGAs

Comparing end-tidal CO2, respiration volume per time (RVT), and average gray matter signal for mapping cerebrovascular reactivity amplitude and delay with breath-hold task BOLD fMRI

Time-Resolved Scanning Ion Conductance Microscopy and Single-Molecule Spectroscopy

SoDaCam: Software-defined Cameras via Single-Photon Imaging

Multi-agent Learning with Privacy Guarantees

Practical computational imaging by use of spatiotemporal light modulation: from simulations to applications in biological microscopy

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

How deep convolutional neural networks lose spatial information with training

A synthetic phase-contrast imaging diagnostic with spatial filtering for gyrokinetic simulations