7 citations · 10 across the 6 of their papers we have counts for
5 papers · 1 filter
Anticipatory Fall Detection in Humans with Hybrid Directed Graph Neural Networks and Long Short-Term Memory
Younggeol Cho, Gokhan Solak, Olivia Nocentini +3
Detecting and preventing falls in humans is a critical component of assistive robotic systems. While significant progress has been made in detecting falls, the prediction of falls…
Graph-based Online Monitoring of Train Driver States via Facial and Skeletal Features
Olivia Nocentini, Marta Lagomarsino, Gokhan Solak +4
Driver fatigue poses a significant challenge to railway safety, with traditional systems like the dead-man switch offering limited and basic alertness checks. This study presents a…
WiFi based Human Fall and Activity Recognition using Transformer based Encoder Decoder and Graph Neural Networks
Younggeol Cho, Elisa Motta, Olivia Nocentini +4
Human pose estimation and action recognition have received attention due to their critical roles in healthcare monitoring, rehabilitation, and assistive technologies. In this study…
Semantic Visual Simultaneous Localization and Mapping: A Survey
Kaiqi Chen, Junhao Xiao, Jialing Liu +6
Visual Simultaneous Localization and Mapping (vSLAM) has achieved great progress in the computer vision and robotics communities, and has been successfully used in many fields such…
CARPE-ID: Continuously Adaptable Re-identification for Personalized Robot Assistance
Federico Rollo, Andrea Zunino, Nikolaos Tsagarakis +2
In today's Human-Robot Interaction (HRI) scenarios, a prevailing tendency exists to assume that the robot shall cooperate with the closest individual or that the scene involves mer…