136 citations · 266 across the 18 of their papers we have counts for
5 papers · 1 filter
Low-Power License Plate Detection and Recognition on a RISC-V Multi-Core MCU-Based Vision System
Lorenzo Lamberti, Manuele Rusci, Marco Fariselli +2
In this paper, we present the first (to the best of our knowledge) demonstration of a low-power MCU-based edge device for Automatic License Plate Recognition (ALPR). The design lev…
MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes
Luca Bompani, Manuele Rusci, Luca Benini +2
Modern smart vision sensors need on-device intelligence to process video streams, as cloud computing is often impractical due to bandwidth, latency, and privacy constraints. Howeve…
Multi-modal On-Device Learning for Monocular Depth Estimation on Ultra-low-power MCUs
Davide Nadalini, Manuele Rusci, Elia Cereda +3
Monocular depth estimation (MDE) plays a crucial role in enabling spatially-aware applications in Ultra-low-power (ULP) Internet-of-Things (IoT) platforms. However, the limited num…
Multi-resolution Rescored ByteTrack for Video Object Detection on Ultra-low-power Embedded Systems
Luca Bompani, Manuele Rusci, Daniele Palossi +2
This paper introduces Multi-Resolution Rescored Byte-Track (MR2-ByteTrack), a novel video object detection framework for ultra-low-power embedded processors. This method reduces th…
Robustifying the Deployment of tinyML Models for Autonomous mini-vehicles
Miguel de Prado, Manuele Rusci, Romain Donze +4
Standard-size autonomous navigation vehicles have rapidly improved thanks to the breakthroughs of deep learning. However, scaling autonomous driving to low-power systems deployed o…