Compression of Multispectral Images: Color (RGB) plus Near-Infrared (NIR)

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The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

This work is concerned with the computation of the action of a matrix function f(A), such as the matrix exponential or the matrix square root, on a vector b. For a general matrix A, this can be done by computing the compression of A onto a suitable Krylov ...

In the development of implantable bioelectronics, the establishment of efficient wireless RF links between implants and external nodes is crucial, providing substantial contributions to the advancement of medical diagnosis, therapies, and basic science. Im ...

While classical in many theoretical settings-and in particular in statistical physics-inspired works-the assumption of Gaussian i.i.d. input data is often perceived as a strong limitation in the context of statistics and machine learning. In this study, we ...

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 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 ...

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 ...

Recent advances in image compression have made it both possible and desirable for image quality to approach the visually lossless range. However, the most commonly used subjective visual quality assessment protocols, e.g. those reported in ITU-T Rec. BT.50 ...

In 1970, Furth and Yoshikawa (1970 Phys. Fluids 13 2593-6) introduced the scalings of adiabatic plasma compression. Basically, if the shape of the external plasma boundary and the aspect ratio are preserved during the compression, then the density, kinetic ...

In the field of image acquisition, Dynamic Vision Sensors (DVS) present an innovative methodology, capturing only the variations in pixel brightness instead of absolute values and thereby revealing unique features. Given that the primary deployment of DVS ...

In this thesis, we explore techniques for addressing the communication bottleneck in data-parallel distributed training of deep learning models. We investigate algorithms that either reduce the size of the messages that are exchanged between workers, or th ...

Neuroscientists seek efficient solutions for deciphering the sophisticated unknowns of the brain. Effective development of complicated brain-related tools is the focal point of research in neuroscience and neurotechnology. Thanks to today's technological a ...

The use of point clouds as an imaging modality has been rapidly growing, motivating research on compression methods to enable efficient transmission and storage for many applications. While compression standards relying on conven- tional techniques such as ...

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 ...

Compression of Multispectral Images: Color (RGB) plus Near-Infrared (NIR)

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Subjective performance evaluation of bitrate allocation strategies for MPEG and JPEG Pleno point cloud compression

Extensions of Peer Prediction Incentive Mechanisms

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

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

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

Room-temperature quantum optomechanics using an ultralow noise cavity

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

SPEEDING UP KRYLOV SUBSPACE METHODS FOR COMPUTING f(A)b VIA RANDOMIZATION

Electromagnetic Radiation of Implantable Antennas

Gaussian universality of perceptrons with random labels

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

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

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

On the assessment of high-quality images: advances on the JPEG AIC-3 activity

Shafranov shift correction to the Furth-Yoshikawa scaling of tokamak adiabatic compression

Evaluation of the impact of lossy compression on event camera-based computer vision tasks

Communication-efficient distributed training of machine learning models

Data Transformation in the Processing of Neuronal Signals: A Powerful Tool to Illuminate Informative Contents

Evaluating the effect of sparse convolutions on point cloud compression

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