activity
20122023
most citedIDNet: Smartphone-based Gait Recognition with Convolutional Neural Networks

260 citations · 809 across the 29 of their papers we have counts for

collaborators
Showing 2022Show all

6 papers · 1 filter

cs.LG2022★ 22 cited

Energy Consumption of Neural Networks on NVIDIA Edge Boards: an Empirical Model

Seyyidahmed Lahmer, Aria Khoshsirat, Michele Rossi +1

Recently, there has been a trend of shifting the execution of deep learning inference tasks toward the edge of the network, closer to the user, to reduce latency and preserve data…

cs.NI2022★ 8 cited

Energy Efficient Deployment and Orchestration of Computing Resources at the Network Edge: a Survey on Algorithms, Trends and Open Challenges

Neda Shalavi, Giovanni Perin, Andrea Zanella +1

Mobile networks are becoming energy hungry, and this trend is expected to continue due to a surge in communication and computation demand. Multi-access Edge Computing (MEC), will e…

eess.SP2022

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…

eess.SP2022★ 30 cited

SPARCS: A Sparse Recovery Approach for Integrated Communication and Human Sensing in mmWave Systems

Jacopo Pegoraro, Jesus Omar Lacruz, Michele Rossi +1

A well established method to detect and classify human movements using Millimeter-Wave ( mmWave) devices is the time-frequency analysis of the small-scale Doppler effect (termed mi…

cs.NI2022★ 15 cited

DeepCSI: Rethinking Wi-Fi Radio Fingerprinting Through MU-MIMO CSI Feedback Deep Learning

Francesca Meneghello, Michele Rossi, Francesco Restuccia

We present DeepCSI, a novel approach to Wi-Fi radio fingerprinting (RFP) which leverages standard-compliant beamforming feedback matrices to authenticate MU-MIMO Wi-Fi devices on t…

cs.LG2022★ 2 cited

SHED: A Newton-type algorithm for federated learning based on incremental Hessian eigenvector sharing

Nicolò Dal Fabbro, Subhrakanti Dey, Michele Rossi +1

There is a growing interest in the distributed optimization framework that goes under the name of Federated Learning (FL). In particular, much attention is being turned to FL scena…