activity
20152024
most citedExtended Report: Fine-grained Recognition of Abnormal Behaviors for Early Detection of Mild Cognitive Impairment

7 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.HC2024

Using Large Language Models to Compare Explainable Models for Smart Home Human Activity Recognition

Michele Fiori, Gabriele Civitarese, Claudio Bettini

Recognizing daily activities with unobtrusive sensors in smart environments enables various healthcare applications. Monitoring how subjects perform activities at home and their ch…

eess.SP2024

Comparing Self-Supervised Learning Techniques for Wearable Human Activity Recognition

Sannara Ek, Riccardo Presotto, Gabriele Civitarese +3

Human Activity Recognition (HAR) based on the sensors of mobile/wearable devices aims to detect the physical activities performed by humans in their daily lives. Although supervise…

cs.LG20232 cited

Neuro-Symbolic Approaches for Context-Aware Human Activity Recognition

Luca Arrotta, Gabriele Civitarese, Claudio Bettini

Deep Learning models are a standard solution for sensor-based Human Activity Recognition (HAR), but their deployment is often limited by labeled data scarcity and models' opacity.…

cs.LG2023

SelfAct: Personalized Activity Recognition based on Self-Supervised and Active Learning

Luca Arrotta, Gabriele Civitarese, Samuele Valente +1

Supervised Deep Learning (DL) models are currently the leading approach for sensor-based Human Activity Recognition (HAR) on wearable and mobile devices. However, training them req…

cs.OH20157 cited

Extended Report: Fine-grained Recognition of Abnormal Behaviors for Early Detection of Mild Cognitive Impairment

Daniele Riboni, Claudio Bettini, Gabriele Civitarese +2

According to the World Health Organization, the rate of people aged 60 or more is growing faster than any other age group in almost every country, and this trend is not going to ch…