9 citations · 35 across the 17 of their papers we have counts for
4 papers · 1 filter
The SERENADE project: Sensor-Based Explainable Detection of Cognitive Decline
Gabriele Civitarese, Michele Fiori, Andrea Arighi +3
Mild Cognitive Impairment (MCI) affects 12-18% of individuals over 60. MCI patients exhibit cognitive dysfunctions without significant daily functional loss. While MCI may progress…
ContextGPT: Infusing LLMs Knowledge into Neuro-Symbolic Activity Recognition Models
Luca Arrotta, Claudio Bettini, Gabriele Civitarese +1
Context-aware Human Activity Recognition (HAR) is a hot research area in mobile computing, and the most effective solutions in the literature are based on supervised deep learning…
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.…
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…