相关论文: Bite-Weight Estimation Using Commercial Ear Buds

Human activity recognition has grown in popularity with its increase of applications within daily lifestyles and medical environments. The goal of having efficient and reliable human activity recognition brings benefits such as accessible…

The increase in awareness of people towards their nutritional habits has drawn considerable attention to the field of automatic food analysis. Focusing on self-service restaurants environment, automatic food analysis is not only useful for…

Distance estimation from audio plays a crucial role in various applications, such as acoustic scene analysis, sound source localization, and room modeling. Most studies predominantly center on employing a classification approach, where…

In the human activity recognition research area, prior studies predominantly concentrate on leveraging advanced algorithms on public datasets to enhance recognition performance, little attention has been paid to executing real-time kitchen…

Real-world machine learning applications often have complex test metrics, and may have training and test data that are not identically distributed. Motivated by known connections between complex test metrics and cost-weighted learning, we…

Engagement is a vital metric in the advertising industry and its automatic estimation has huge commercial implications. This work presents a basic and simple framework for engagement estimation using EEG (electroencephalography) data…

Eating monitoring has remained an open challenge in medical research for years due to the lack of non-invasive sensors for continuous monitoring and the reliable methods for automatic behavior detection. In this paper, we present a pilot…

Compressed sensing typically deals with the estimation of a system input from its noise-corrupted linear measurements, where the number of measurements is smaller than the number of input components. The performance of the estimation…

In recent years, wearable devices have become more common to capture a wide range of health behaviors, especially for physical activity and sedentary behavior. These sensor-based measures are deemed to be objective and thus less prone to…

This article reviews bias-correction models for measurement error of exposure variables in the field of nutritional epidemiology. Measurement error usually attenuates estimated slope towards zero. Due to the influence of measurement error,…

Rapid and accurate body weight estimation is critical in emergency medical care, as it directly influences treatment decisions, such as drug dosing, defibrillation energy selection, and fluid resuscitation. Traditional methods such as…

In this paper, we seek solutions for reducing the computation complexity of transformer-based models for speech representation learning. We evaluate 10 attention algorithms; then, we pre-train the transformer-based model with those…

Computer vision has been introduced to estimate calories from food images. But current food image data sets don't contain volume and mass records of foods, which leads to an incomplete calorie estimation. In this paper, we present a novel…

Smartwatches are widely used to estimate caloric expenditure for weight management, clinical decision making, and public health monitoring. These devices combine photoplethysmography, accelerometry, and proprietary algorithms. However,…

Food recognition is an important task for a variety of applications, including managing health conditions and assisting visually impaired people. Several food recognition studies have focused on generic types of food or specific cuisines,…

Measurement error can often be harmful when estimating causal effects. Two scenarios in which this is the case are in the estimation of (a) the average treatment effect when confounders are measured with error and (b) the natural indirect…

While 3D human body modeling has received much attention in computer vision, modeling the acoustic equivalent, i.e. modeling 3D spatial audio produced by body motion and speech, has fallen short in the community. To close this gap, we…

As a response to the global COVID-19 surge in 2020, many countries have implemented lockdown or stay-at-home policies. If, however, the contact persons of every infected patient could be identified, the number of virus transmissions could…

Obesity is a serious issue in the modern society and is often associated to significantly reduced quality of life. Current research conducted to explore obesity-related neurological evidences using electroencephalography (EEG) data are…

Regular nutrient intake monitoring in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition (DRM). Although several methods to estimate nutrient intake have been developed, there is still a clear…