3 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
End-to-end Automated Deep Neural Network Optimization for PPG-based Blood Pressure Estimation on Wearables
Francesco Carlucci, Giovanni Pollo, Xiaying Wang +6
Photoplethysmography (PPG)-based blood pressure (BP) estimation is a challenging task, particularly on resource-constrained wearable devices. However, fully on-board processing is…
Coupling Neural Networks and Physics Equations For Li-Ion Battery State-of-Charge Prediction
Giovanni Pollo, Alessio Burrello, Enrico Macii +3
Estimating the evolution of the battery's State of Charge (SoC) in response to its usage is critical for implementing effective power management policies and for ultimately improvi…
VARADE: a Variational-based AutoRegressive model for Anomaly Detection on the Edge
Alessio Mascolini, Sebastiano Gaiardelli, Francesco Ponzio +5
Detecting complex anomalies on massive amounts of data is a crucial task in Industry 4.0, best addressed by deep learning. However, available solutions are computationally demandin…
Neuro-symbolic Empowered Denoising Diffusion Probabilistic Models for Real-time Anomaly Detection in Industry 4.0
Luigi Capogrosso, Alessio Mascolini, Federico Girella +10
Industry 4.0 involves the integration of digital technologies, such as IoT, Big Data, and AI, into manufacturing and industrial processes to increase efficiency and productivity. A…