66 citations · 105 across the 12 of their papers we have counts for
13 papers
A system for objectively measuring behavior and the environment to support large-scale studies on childhood obesity
Vasileios Papapanagiotou, Ioannis Sarafis, Leonidas Alagialoglou +3
Advances in IoT technologies combined with new algorithms have enabled the collection and processing of high-rate multi-source data streams that quantify human behavior in a fine-g…
Listen2YourHeart: A Self-Supervised Approach for Detecting Murmur in Heart-Beat Sounds
Aristotelis Ballas, Vasileios Papapanagiotou, Anastasios Delopoulos +1
Heart murmurs are abnormal sounds present in heartbeats, caused by turbulent blood flow through the heart. The PhysioNet 2022 challenge targets automatic detection of murmur from a…
Intake Monitoring in Free-Living Conditions: Overview and Lessons we Have Learned
Christos Diou, Konstantinos Kyritsis, Vasileios Papapanagiotou +1
The progress in artificial intelligence and machine learning algorithms over the past decade has enabled the development of new methods for the objective measurement of eating, inc…
An improved neural network model for treatment effect estimation
Niki Kiriakidou, Christos Diou
Nowadays, in many scientific and industrial fields there is an increasing need for estimating treatment effects and answering causal questions. The key for addressing these problem…
Self-Supervised Feature Learning of 1D Convolutional Neural Networks with Contrastive Loss for Eating Detection Using an In-Ear Microphone
Vasileios Papapanagiotou, Christos Diou, Anastasios Delopoulos
The importance of automated and objective monitoring of dietary behavior is becoming increasingly accepted. The advancements in sensor technology along with recent achievements in…
Recognition of food-texture attributes using an in-ear microphone
Vasileios Papapanagiotou, Christos Diou, Janet van den Boer +2
Food texture is a complex property; various sensory attributes such as perceived crispiness and wetness have been identified as ways to quantify it. Objective and automatic recogni…
A Data Driven End-to-end Approach for In-the-wild Monitoring of Eating Behavior Using Smartwatches
Konstantinos Kyritsis, Christos Diou, Anastasios Delopoulos
The increased worldwide prevalence of obesity has sparked the interest of the scientific community towards tools that objectively and automatically monitor eating behavior. Despite…
Collecting big behavioral data for measuring behavior against obesity
Vasileios Papapanagiotou, Ioannis Sarafis, Christos Diou +3
Obesity is currently affecting very large portions of the global population. Effective prevention and treatment starts at the early age and requires objective knowledge of populati…
Inferring the Spatial Distribution of Physical Activity in Children Population from Characteristics of the Environment
Ioannis Sarafis, Christos Diou, Vasileios Papapanagiotou +2
Obesity affects a rising percentage of the children and adolescent population, contributing to decreased quality of life and increased risk for comorbidities. Although the major ca…
BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment
Christos Diou, Ioannis Sarafis, Vasileios Papapanagiotou +28
Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention s…
A Methodology for Obtaining Objective Measurements of Population Obesogenic Behaviors in Relation to the Environment
Christos Diou, Ioannis Sarafis, Vasileios Papapanagiotou +2
The way we eat and what we eat, the way we move and the way we sleep significantly impact the risk of becoming obese. These aspects of behavior decompose into several personal beha…
Span error bound for weighted SVM with applications in hyperparameter selection
Ioannis Sarafis, Christos Diou, Anastasios Delopoulos
Weighted SVM (or fuzzy SVM) is the most widely used SVM variant owning its effectiveness to the use of instance weights. Proper selection of the instance weights can lead to increa…
Learning Local Feature Aggregation Functions with Backpropagation
Angelos Katharopoulos, Despoina Paschalidou, Christos Diou +1
This paper introduces a family of local feature aggregation functions and a novel method to estimate their parameters, such that they generate optimal representations for classific…