Publications related to Influence of Context and Content on Tone-mapping Operators

Extensions of Peer Prediction Incentive Mechanisms

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

An Ultralow-Power Triaxial MEMS Accelerometer With High-Voltage Biasing and Electrostatic Mismatch Compensation

Yimai Peng, Li Xu, Kyojin Choo

This article presents a triaxial micro electromechani-cal system (MEMS) capacitive accelerometer using a high-voltage biasing technique to achieve high resolution with ultralow power. The accelerometer system generates a differential pair of high voltages ...

Ieee-Inst Electrical Electronics Engineers Inc2024

Three-wave-mixing quantum-limited kinetic inductance parametric amplifier operating at 6 T near 1 K

Camille René Charles Roy, Simone Frasca, Guillaume Beaulieu, Pasquale Scarlino

Parametric amplifiers play a crucial role in modern quantum technology by enabling the enhancement of weak signals with minimal added noise. Traditionally, Josephson junctions have been the primary choice for constructing parametric amplifiers. Nevertheles ...

American Physical Society (APS)2024

Ultrahigh-quality-factor micro- and nanomechanical resonators using dissipation dilution

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari

Mechanical resonators are widely used in sensors, transducers and optomechanical systems, where mechanical dissipation sets the ultimate limit to performance. Over the past 15 years, the quality factors in strained mechanical resonators have increased by f ...

Nature Portfolio2024

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Ksenia Briling

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

A state-of-the-art, systematic review of indoor environmental quality studies in work-from-home settings

Giorgia Chinazzo

The COVID-19 pandemic has led to a significant increase in working from home worldwide, making the workfrom-home (WFH) setting a crucial context for studying the influence of indoor environmental quality (IEQ) on workers' well-being and productivity. A nar ...

Pergamon-Elsevier Science Ltd2024

Room-temperature quantum optomechanics using an ultralow noise cavity

Tobias Kippenberg, Nils Johan Engelsen, Alberto Beccari, Guanhao Huang

At room temperature, mechanical motion driven by the quantum backaction of light has been observed only in pioneering experiments in which an optical restoring force controls the oscillator stiffness1,2. For solid-state mechanical resonators in which oscil ...

Nature Portfolio2024

Performance investigation of cameras using HDR sensors for daylight glare evaluations

Jan Wienold, Geraldine Cai Ting Quek, Dong Hyun Kim

This study presents a novel framework for evaluating the luminance measurement capabilities of High Dynamic Range (HDR) sensor cameras in indoor glare conditions. Results indicate that the practical usage range of the CSEM VIP camera is significantly lower ...

International Commission on Illumination2023

Dynamism in the context of views out: A literature review

Marilyne Andersen, Caroline Karmann, Yunjoung Cho

Previous studies have shown that access to a satisfactory view to the outside with sufficient daylight is essential for building occupants' health and well-being. It has also been suggested that certain features of visual content improve view-out quality, ...

2023

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Panayiotis Danassis, Ljubomir Rokvic

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

Burst Vision Using Single-Photon Cameras

Edoardo Charbon, Paul Mos, Mohit Gupta

Single-photon avalanche diodes (SPADs) are novel image sensors that record the arrival of individual photons at extremely high temporal resolution. In the past, they were only available as single pixels or small-format arrays, for various active imaging ap ...

IEEE COMPUTER SOC2023

On the Performance of Subjective Visual Quality Assessment Protocols for Nearly Visually Lossless Image Compression

Touradj Ebrahimi, Davi Nachtigall Lazzarotto, Michela Testolina

The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduce ...

2023

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Boi Faltings, Naman Goel

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

2023

Blue Brain Nexus: An open, secure, scalable system for knowledge graph management and data-driven science

Henry Markram, Henry Genet, Alejandra Garcia Rojas Martinez, Sean Lewis Hill, Huanxiang Lu, Mohameth François Sy, Samuel Claude Kerrien, Michaël Fernand Paul Dupont, Silvia Rosario Jimenez Tejeda, Bogdan Roman, Ian Lavriushev, Anna-Kristin Kaufmann, Didac Montero Mendez, Wojciech Adam Wajerowicz, Pierre-Alexandre Fonta, Kenneth William Pirman, Julien Antonin Machon, Jonathan Raël Lurie, Dhanesh Neela Mana, Natalia Stafeeva, Alexander Désiré Ulbrich, Carolina Johanna Elisabeth Lindqvist

Modern data-driven science often consists of iterative cycles of data discovery, acquisition, preparation, analysis, model building and validation leading to knowledge discovery as well as dissemination at scale. The unique challenges of building and simul ...

2023

JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range

Touradj Ebrahimi, Vlad Hosu, Davi Nachtigall Lazzarotto, Michela Testolina

Visual data play a crucial role in modern society, and the rate at which images and videos are acquired, stored, and exchanged every day is rapidly increasing. Image compression is the key technology that enables storing and sharing of visual content in an ...

2023

Caching and Neutrality

Aikaterini Argyraki, Pavlos Nikolopoulos, Muhammad Abdullah

We are used to defining network neutrality as absence of traffic differentiation, like policing or shaping. These mechanisms, however, are often not what determines end-users’ quality of experience (QoE). Most content today is accessed through edge caches, ...

ACM Association for Computing Machinery2023

Intelligent RF System for Ultra Low Power Spectrum Sensing with Machine Learning

Naci Pekçokgüler

The crowdedness of the RF spectrum constitutes problems in communication, however it also accommodates large amount of useful information. This information can be used to determine existing signals and operating contexts. However, spectrum condition varies ...

EPFL2024

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning

Jean-Philippe Thiran, Roser Vinals Terres

Ultrafast ultrasound imaging, characterized by high frame rates, generates low-quality images. Convolutional neural networks (CNNs) have demonstrated great potential to enhance image quality without compromising the frame rate. However, CNNs have been most ...

2023

Metasurface-stabilized optical microcavities

Ileana-Cristina Benea-Chelmus

Cavities concentrate light and enhance its interaction with matter. Confining to microscopic volumes is necessary for many applications but space constraints in such cavities limit the design freedom. Here we demonstrate stable optical microcavities by cou ...

Nature Portfolio2023

NbN films with high kinetic inductance for high-quality compact superconducting resonators

Edoardo Charbon, Simone Frasca, Pasquale Scarlino, Vincent Jean Yves Jouanny, Fabian Oppliger, Fabrizio Minganti, Marco Scigliuzzo, Roberto Musio

Niobium nitride (NbN) is a particularly promising material for quantum technology applications, as it shows the degree of reproducibility necessary for large-scale superconducting circuits. We demonstrate that resonators based on NbN thin films present a o ...

American Physical Society (APS)2023