78 citations · 120 across the 11 of their papers we have counts for
8 papers · 1 filter
Human Tracking with mmWave Radars: a Deep Learning Approach with Uncertainty Estimation
Jacopo Pegoraro, Michele Rossi
mmWave radars have recently gathered significant attention as a means to track human movement within indoor environments. Widely adopted Kalman filter tracking methods experience p…
Real-time People Tracking and Identification from Sparse mm-Wave Radar Point-clouds
Jacopo Pegoraro, Michele Rossi
Mm-wave radars have recently gathered significant attention as a means to track human movement and identify subjects from their gait characteristics. A widely adopted method to per…
Multi-Person Continuous Tracking and Identification from mm-Wave micro-Doppler Signatures
Jacopo Pegoraro, Francesca Meneghello, Michele Rossi
In this work, we investigate the use of backscattered mm-wave radio signals for the joint tracking and recognition of identities of humans as they move within indoor environments.…
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…