260 citations · 809 across the 29 of their papers we have counts for
5 papers · 1 filter
Seq2Seq RNN based Gait Anomaly Detection from Smartphone Acquired Multimodal Motion Data
Riccardo Bonetto, Mattia Soldan, Alberto Lanaro +2
Smartphones and wearable devices are fast growing technologies that, in conjunction with advances in wireless sensor hardware, are enabling ubiquitous sensing applications. Wearabl…
Mobile Traffic Classification through Physical Channel Fingerprinting: a Deep Learning Approach
Hoang Duy Trinh, Angel Fernandez Gambin, Lorenza Giupponi +2
The automatic classification of applications and services is an invaluable feature for new generation mobile networks. Here, we propose and validate algorithms to perform this task…
Deep Learning Techniques for Improving Digital Gait Segmentation
Matteo Gadaleta, Giulia Cisotto, Michele Rossi +3
Wearable technology for the automatic detection of gait events has recently gained growing interest, enabling advanced analyses that were previously limited to specialist centres a…
Online Resource Management in Energy Harvesting BS Sites through Prediction and Soft-Scaling of Computing Resources
Thembelihle Dlamini, Angel Fernandez Gambin, Daniele Munaretto +1
Multi-Access Edge Computing (MEC) is a paradigm for handling delay sensitive services that require ultra-low latency at the access network. With it, computing and communications ar…
Online Supervisory Control and Resource Management for Energy Harvesting BS Sites Empowered with Computation Capabilities
Thembelihle Dlamini, Angel Fernandez Gambin, Daniele Munaretto +1
The convergence of communication and computing has lead to the emergence of Multi-access Edge Computing (MEC), where computing resources (supported by Virtual Machines (VMs)) are d…