17 citations · 43 across the 16 of their papers we have counts for
9 papers · 1 filter
Few-Shot Adaptation for Anomalous Sound Detection at Low False-Positive Rate
Simone Lugani, Christof Pichler, Hannes Wegleiter +3
Reliable fault detection is crucial for industrial machinery in large-scale facilities, where unexpected failures can cause costly downtime and production interruptions. Although a…
RepTC: Representation-Aware Optimization for Efficient Traffic Classification on Edge IoT Devices
Adel Chehade, Edoardo Ragusa, Paolo Gastaldo +1
Traffic classification (TC) is crucial to secure Internet of Things (IoT) networks, whose edge nodes often operate under privacy, bandwidth, and energy constraints. Yet, encrypted…
Lightweight Neural Networks for Affordance Segmentation: Enhancement of the Decoder Module
Simone Lugani, Edoardo Ragusa, Rodolfo Zunino +1
The deployment of deep neural networks for visual affordance segmentation on wearable robots poses may prove critical, due to some conflicting aspects of the problem. On one hand,…
Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras
Edoardo Ragusa, Giovanni Paolo Canuti, Simone Lugani +2
While depth sensors have the potential to complement RGB data for affordance segmentation in wearable robots, their usage seems to remain underexplored. The paper proposes two appr…
BearingNAS: Obtaining In-Sensor Intelligent Fault Diagnosis Systems for Bearings Using a Laptop
Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +2
This paper introduces BearingNAS, a Hardware-Aware Neural Architecture Search (HW-NAS) framework designed to shift the intelligence directly onto the sensor die via in-sensor proce…
An affordable hardware-aware neural architecture search for deploying convolutional neural networks on ultra-low-power computing platforms
Andrea Mattia Garavagno, Edoardo Ragusa, Antonio Frisoli +1
Hardware-aware neural architecture search (HW-NAS) allows the integration of Convolutional Neural Networks (CNNs) in microcontrollers devices by automatically designing neural arch…
On-Device Neural Architecture Search
Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +2
This paper proposes a new approach to near-sensor computing, in which a lightweight Neural Architecture Search (NAS) is performed directly on the deployment device to find the best…
Running hardware-aware neural architecture search on embedded devices under 512MB of RAM
Andrea Mattia Garavagno, Edoardo Ragusa, Paolo Gastaldo +1
This document proposes a novel approach to hardware-aware neural architecture search (HW NAS) that considers the resources available on the computing platform running it, enabling…
The data heat island effect: quantifying the impact of AI data centers in a warming world
Andrea Marinoni, Erik Cambria, Weisi Lin +6
The strong and continuous increase of AI-based services leads to the steady proliferation of AI data centres worldwide with the unavoidable escalation of their power consumption. I…