2 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 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…