5 papers
Sparse Spike Encoding of Channel Responses for Energy Efficient Human Activity Recognition
Eleonora Cicciarella, Riccardo Mazzieri, Jacopo Pegoraro +1
ISAC enables pervasive monitoring, but modern sensing algorithms are often too complex for energy-constrained edge devices. This motivates the development of learning techniques th…
ADMM-Based Training for Spiking Neural Networks
Giovanni Perin, Cesare Bidini, Riccardo Mazzieri +1
In recent years, spiking neural networks (SNNs) have gained momentum due to their high potential in time-series processing combined with minimal energy consumption. However, they s…
Spatiotemporal Radar Gesture Recognition with Hybrid Spiking Neural Networks: Balancing Accuracy and Efficiency
Riccardo Mazzieri, Eleonora Cicciarella, Jacopo Pegoraro +2
Radar-based Human Activity Recognition (HAR) offers privacy and robustness over camera-based methods, yet remains computationally demanding for edge deployment. We present the firs…
Open-Set Gait Recognition from Sparse mmWave Radar Point Clouds
Riccardo Mazzieri, Jacopo Pegoraro, Michele Rossi
The adoption of Millimeter-Wave (mmWave) radar devices for human sensing, particularly gait recognition, has recently gathered significant attention due to their efficiency, resili…
LightSNN: Lightweight Architecture Search for Sparse and Accurate Spiking Neural Networks
Yesmine Abdennadher, Giovanni Perin, Riccardo Mazzieri +2
Spiking Neural Networks (SNNs) are highly regarded for their energy efficiency, inherent activation sparsity, and suitability for real-time processing in edge devices. However, mos…