Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

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Recent works in hand-object reconstruction mainly focus on the single-view and dense multi-view settings. On the one hand, single-view methods can leverage learned shape priors to generalise to unseen objects but are prone to inaccuracies due to occlusions ...

Wearable and implantable medical devices are of great importance in diagnosis and treatment as they provide continuous monitoring and data collection. Considering the comfort of the patient and ease-of-operation, these devices require wireless data transmi ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Distributed learning is the key for enabling training of modern large-scale machine learning models, through parallelising the learning process. Collaborative learning is essential for learning from privacy-sensitive data that is distributed across various ...

Photometric stereo, a computer vision technique for estimating the 3D shape of objects through images captured under varying illumination conditions, has been a topic of research for nearly four decades. In its general formulation, photometric stereo is an ...

Buildings play a pivotal role in the ongoing worldwide energy transition, accounting for 30% of the global energy consumption. With traditional engineering solutions reaching their limits to tackle such large-scale problems, data-driven methods and Machine ...

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...

A frequency scaling governor is critical for the performance management of cloud servers, as it enhances energy efficiency and helps to control operational temperatures, thereby ensuring system reliability. However, our in-depth analysis of the application ...

Fluorescence lifetime imaging (FLI) has been receiving increased attention in recent years as a powerful diagnostic technique in biological and medical research. However, existing FLI systems often suffer from a tradeoff between processing speed, accuracy, ...

This repository contains microphysics routines, scripts, and processed data from the Weather Research and Forecasting (WRF) model simulations presented in the paper "RaFSIP: Parameterizing ice multiplication in models using a machine learning approach", by ...

Nuclear power is a powerful technology that plays an important role in the fight against climate change, and research is continuously engaged in studies that could further improve its safety. After the Fukushima accident, Accident Tolerant Fuels research h ...

Deep learning has revolutionized the field of computer vision, a success largely attributable to the growing size of models, datasets, and computational power. Simultaneously, a critical pain point arises as several computer vision applications are deploye ...

Digital twins are virtual models of physical objects or systems that enable real-time monitoring and analysis. In the ﬁeld of stone masonry buildings, digital twins can be used to assess damage, predict maintenance needs, and opti- mize building performanc ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Because building-integrated photovoltaic (BIPV) modules are fully integrated into a building envelope, the back of the module can be exposed to little or no ventilation, resulting in increased operating temperatures. As the temperature increases, the perfo ...

The auxiliary power supply for medium voltage converters requires high insulation capability between the source and the load. Inductive power transfer technology, with an air gap between the primary and secondary coil, offers such high insulation capabilit ...

Electric vehicles (EVs) are becoming more popular due to environmental consciousness. The limited availability of charging stations (CSs), compared to the number of EVs on the road, has led to increased range anxiety and a higher frequency of CS queries du ...

We measure the metallicities of 374 red giant branch (RGB) stars in the isolated, quenched dwarf galaxy Tucana using Hubble Space Telescope (HST) narrow-band (F395N) Calcium H & K (CaHK) imaging. Our sample is a factor of similar to 7 similar to 7 larger t ...

This study aims to determine whether 1) individuals with treatment-resistant schizophrenia display early cognitive impairment compared to treatment-responders and healthy controls and 2) N-methyl-D-aspartate-receptor hypofunction is an underlying mechanism ...

Toward contactless human thermal monitoring: A framework for Machine Learning-based human thermo-physiology modeling augmented with computer vision

Chattez avec Graph Search

Sparse multi-view hand-object reconstruction for unseen environments

An area efficient inductorless super-regenerative receiver front-end for biomedical implant devices

Robust machine learning for neuroscientific inference

Optimization Algorithms for Decentralized, Distributed and Collaborative Machine Learning

Aggregating Spatial and Photometric Context for Photometric Stereo

Fusing Pre-existing Knowledge and Machine Learning for Enhanced Building Thermal Modeling and Control

Differentially private multi-agent constraint optimization

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Is the powersave governor really saving power?

Coupling a recurrent neural network to SPAD TCSPC systems for real-time fluorescence lifetime imaging

Data and scripts for the RaFSIP scheme

Innovative thermophysical characterization of an ATF composite cladding: the case of silicon carbide

Fast and Future: Towards Efficient Forecasting in Video Semantic Segmentation

Digital Twins of Stone Masonry Buildings for Damage Assessment

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Correlating long-term performance and aging behaviour of building integrated PV modules

Modeling and optimization of PCB coils for inductive power transfer systems

A Privacy-Preserving Querying Mechanism with High Utility for Electric Vehicles

Stellar Metallicities and Gradients in the Isolated, Quenched Low-mass Galaxy Tucana

Neurocognition and NMDAR co-agonists pathways in individuals with treatment resistant first-episode psychosis: a 3-year follow-up longitudinal study