2 citations · 3 across the 7 of their papers we have counts for
8 papers
Transformer-based Neural Beamforming for Real-Time Speech Enhancement on Smart Low-Power Hearable Devices
Luca Bompani, Marco Fariselli, Giovanni Oltrecolli +1
Accurate, efficient, and low-latency spatial beamforming is a key component in emerging smart hearable devices, enhancing speech while suppressing noise and interference. However,…
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…
Accelerating Image-based Pest Detection on a Heterogeneous Multi-core Microcontroller
Luca Bompani, Luca Crupi, Daniele Palossi +5
The codling moth pest poses a significant threat to global crop production, with potential losses of up to 80% in apple orchards. Special camera-based sensor nodes are deployed in…
Deeploy: Enabling Energy-Efficient Deployment of Small Language Models On Heterogeneous Microcontrollers
Moritz Scherer, Luka Macan, Victor Jung +5
With the rise of Embodied Foundation Models (EFMs), most notably Small Language Models (SLMs), adapting Transformers for edge applications has become a very active field of researc…
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…
Multi-sensory Anti-collision Design for Autonomous Nano-swarm Exploration
Mahyar Pourjabar, Manuele Rusci, Luca Bompani +4
This work presents a multi-sensory anti-collision system design to achieve robust autonomous exploration capabilities for a swarm of 10 cm-side nano-drones operating on object dete…
A Survey on Design Methodologies for Accelerating Deep Learning on Heterogeneous Architectures
Serena Curzel, Fabrizio Ferrandi, Leandro Fiorin +15
Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the design of heterogeneous High-Performanc…
Bio-inspired Autonomous Exploration Policies with CNN-based Object Detection on Nano-drones
Lorenzo Lamberti, Luca Bompani, Victor Javier Kartsch +3
Nano-sized drones, with palm-sized form factor, are gaining relevance in the Internet-of-Things ecosystem. Achieving a high degree of autonomy for complex multi-objective missions…