Publications related to Bits from Photons

Analysis of photosensor frontends for biomedical applications: a focus on noise

Photosensing has proven to be highly useful in biomedical research and medical care. Being able to detect and quantify the light emitted by fluorescent or bioluminescent reporters has significantly participated in the development of new cancer treatments a ...

EPFL2019

An Easily Computable Error Estimator In Space And Time For The Wave Equation

Marco Picasso, Olga Gorynina

We propose a cheaper version of a posteriori error estimator from Gorynina et al. (Namer. Anal. (2017)) for the linear second-order wave equation discretized by the Newmark scheme in time and by the finite element method in space. The new estimator preserv ...

EDP Sciences2019

High-dynamic-range imaging with photon-counting arrays (Conference Presentation)

Edoardo Charbon, Claudio Bruschini, Ivan Michel Antolovic

We present a comprehensive analysis to guide the use of the nonlinear photon response in photon-counting arrays to extend their optical dynamic range far beyond 1/Tdead, where Tdead is the pixel dead time after photon detection, so as to achieve a high dyn ...

2019

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

Jean-Philippe Thiran, Erick Jorge Canales Rodriguez, Gabriel Girard, Marco Pizzolato, Jonathan Rafael Patino Lopez, Thomas Yu

Probabilistic parameter estimation in model fitting runs the gamut from maximum likelihood or maximum a posteriori point estimates from optimization to Markov Chain Monte Carlo (MCMC) sampling. The latter, while more computationally intensive, generally pr ...

SPRINGER INTERNATIONAL PUBLISHING AG2019

Pixel sensor cell for cmos image sensors with enhanced conversion gain at high dynamic range capability

Assim Boukhayma

The present invention relates to a pixel sensor cell (1) for a CMOS sensor device comprising: - a photodiode (11) for generating photoelectrons; - a first transfer transistor (12) coupling the photodiode (11) with an intermediate node (IN) and configured t ...

2019

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

Many decision problems in science, engineering and economics are affected by uncertain parameters whose distribution is only indirectly observable through samples. The goal of data-driven decision-making is to learn a decision from finitely many training s ...

2019

Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model

Andrea Rinaldo, Bettina Schaefli, Ana Clara Pereira Barbosa Santos

Streamflow recession analysis characterizes the storage-outflow relationship in catchments. This relationship, which typically follows a power law, summarizes all catchment-scale subsurface hydrological processes and has long been known to be a key descrip ...

2019

Design and Validation of a Compact Embedded Photometric Device for Real-time Daylighting Computing in Office Buildings

Jean-Louis Scartezzini, Jérôme Henri Kämpf, Yujie Wu

Studies have shown that the exposure to daylight can have substantial visual/non-visual benefits for building occupants. To optimise daylighting provision while maintaining a comfortable visual environment, daylighting control systems have been investigate ...

2019

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Edoardo Charbon, Chunmin Zhang, Preethi Padmanabhan

Direct time-of-flight (DTOF) is a prominent depth sensing method in light detection and ranging (LiDAR) applications. Single-photon avalanche diode (SPAD) arrays integrated in DTOF sensors have demonstrated excellent ranging and 3D imaging capabilities, ma ...

2019

A Modular, Direct Time-of-Flight Depth Sensor in 45/65-nm 3-D-Stacked CMOS Technology

Edoardo Charbon, Myung Jae Lee, Preethi Padmanabhan, Augusto Ronchini Ximenes

This article introduces a modular, direct time-of-flight (TOF) depth sensor. Each module is digitally synthesized and features a 2

\times

(8

\times

8) single-photon avalanche diode (SPAD) pixel array, an edge-sensitive decision tree, a shared time-to ...

2019

Bits from Photons

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Analysis of photosensor frontends for biomedical applications: a focus on noise

An Easily Computable Error Estimator In Space And Time For The Wave Equation

High-dynamic-range imaging with photon-counting arrays (Conference Presentation)

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

Pixel sensor cell for cmos image sensors with enhanced conversion gain at high dynamic range capability

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning

Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model

Design and Validation of a Compact Embedded Photometric Device for Real-time Daylighting Computing in Office Buildings

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

A Modular, Direct Time-of-Flight Depth Sensor in 45/65-nm 3-D-Stacked CMOS Technology

An Easily Computable Error Estimator In Space And Time For The Wave Equation

High-dynamic-range imaging with photon-counting arrays (Conference Presentation)

Robust Biophysical Parameter Estimation with a Neural Network Enhanced Hamiltonian Markov Chain Monte Carlo Sampler

Pixel sensor cell for cmos image sensors with enhanced conversion gain at high dynamic range capability

A Modular, Direct Time-of-Flight Depth Sensor in 45/65-nm 3-D-Stacked CMOS Technology

Estimation of streamflow recession parameters: New insights from an analytic streamflow distribution model

Analysis of photosensor frontends for biomedical applications: a focus on noise

Design and Validation of a Compact Embedded Photometric Device for Real-time Daylighting Computing in Office Buildings

Modeling and Analysis of a Direct Time-of-Flight Sensor Architecture for LiDAR Applications

Wasserstein Distributionally Robust Optimization: Theory and Applications in Machine Learning