Resolution and penetration depth of reflection-mode time-domain near infrared optical tomography using a ToF SPAD camera

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

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 ...

This paper presents a comparison of machine learning (ML) methods used for three-dimensional localization of partial discharges (PD) in a power transformer tank. The study examines ML and deep learning (DL) methods, ranging from support vector machines (SV ...

Applications demanding imaging at low-light conditions at near-infrared (NIR) and short-wave infrared (SWIR) wavelengths, such as quantum information science, biophotonics, space imaging, and light detection and ranging (LiDAR), have accelerated the develo ...

Low-level light detection with high spatial and timing accuracy is a growing area of interest by virtue of applications such as light detection and ranging (LiDAR), biomedical imaging, time-resolved Raman spectroscopy, and quantum applications. Single-phot ...

Dynamic downscaling of atmospheric forcing data to the hectometer resolution has shown increases in accuracy for landsurface models, but at great computational cost. Here we present a validation of a novel intermediate complexity atmospheric model, HICAR, ...

Battery health prediction is significant while challenging for intelligent battery management. This article proposes a general framework for both short-term and long-term predictions of battery health under unseen dynamic loading and temperature conditions ...

High-grade gliomas (HGG) are the most common and most aggressive primary tumors of the brain. Despite recent advances in neuro-oncology survival of these tumors remains around 12-15 months. The first-line of treatment is surgical resection. However, due to ...

Electrically connected and plasmonically enhanced molecular junctions combine the optical functionalities of high field confinement and enhancement (cavity function), and of high radiative efficiency (antenna function) with the electrical functionalities o ...

This thesis uses femtosecond laser spectroscopy in studying strong correlation in condensed matters that are pertinent to future technology: a wide bandgap perovskite and a quantum material, with the employment of ultrafast time-resolved spectroscopy in th ...

Infrared and Raman spectroscopies are ubiquitous techniques employed in many experimental laboratories, thanks to their fast and non-destructive nature able to capture materials' features as spectroscopic fingerprints. Nevertheless, these measurements freq ...

Cancer is among the leading causes of death worldwide, and as knowledge of the disease continues to grow there is an increasing interest towards precision medicine: more specifically towards the theranostics field, i.e the development of targeted molecular ...

Chip -scale optical frequency combs enable the generation of highly -coherent pulsed light at gigahertz-level repetition rates, with potential technological impact ranging from telecommunications to sensing and spectroscopy. In combination with techniques ...

The integration of the new plasma position reflectometer in the RFX-mod2 experiment (the upgraded version of the previous RFX-mod that operated until 2015) is presented in this contribution. Particular attention has been devoted to the high field side subs ...

Glacial moulins (cylindrical meltwater drainage shafts) provide valuable insights into glacier dynamics, but are inaccessible and hazardous environments for humans to study. Exploring them using passive sensor probes has revealed their complex geometry, wh ...

This paper presents the new 2D electrostatic particle -in -cell code FENNECS developed to study the formation of magnetized non -neutral plasmas in geometries with azimuthal symmetry. This code has been developed in the domain of gyrotron electron gun desi ...

Tightly-coupled sensor orientation, i.e. the simultaneous processing of temporal (GNSS and raw inertial) and spatial (image and lidar) constraints in a common adjustment, has demonstrated significant improvement in the quality of attitude determination wit ...

Human thermo-physiology models (HTPM) are useful tools to assess dynamic and non-uniform human thermal states. However, they are developed based on the physiological data of an average person. In this paper, we present a detailed evaluation of two sophisti ...

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 ...

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

Many methods exist to model snow densification in order to calculate the depth of a single snow layer or the depth of the total snow cover from its mass. Most of these densification models need to be tightly integrated with an accumulation and melt model a ...

Resolution and penetration depth of reflection-mode time-domain near infrared optical tomography using a ToF SPAD camera

Chattez avec Graph Search

Spectral Estimators for High-Dimensional Matrix Inference

Partial discharge localization in power transformer tanks using machine learning methods

Silicon CMOS and InGaAs(P)/InP SPADs for NIR/SWIR detection

Advanced Silicon and SWIR Single-Photon Avalanche Diodes: Design, Simulation, and Characterization

Intermediate complexity atmospheric modeling in complex terrain: is it right?

Health Prediction for Lithium-Ion Batteries Under Unseen Working Conditions

A fatty-acid based probe for near-infrared fluorescence guided surgery of glioblastoma

Light Emission and Conductance Fluctuations in Electrically Driven and Plasmonically Enhanced Molecular Junctions

Investigating Non-equilibrium Physics in Wide Bandgap Semiconductors and Quantum Materials via Ultrafast Spectroscopy

Automated all-functionals infrared and Raman spectra

Functionalization of harmonic nanoparticles for drug release and multimodal imaging applications

Dissipative Kerr soliton generation at 2μm in a silicon nitride microresonator

Technology challenges and integration of the plasma position reflectometer in RFX-mod2

Into the ice: Exploration and data capturing in glacial moulins by a tethered robot

FENNECS: a novel particle-in-cell code for simulating the formation of magnetized non-neutral plasmas trapped by electrodes of complex geometries

Airborne sensor fusion: Expected accuracy and behavior of a concurrent adjustment

Modeling local thermal responses of individuals: Validation of advanced human thermo-physiology models

Quantization for Decentralized Learning Under Subspace Constraints

Timing and spatial selection bias in rapid extreme event attribution

An empirical model to calculate snow depth from daily snow water equivalent: SWE2HS 1.0