A Tiny Transformer-Based Anomaly Detection Framework for IoT Solutions

A Tiny Transformer-Based Anomaly Detection Framework for IoT Solutions

The widespread proliferation of Internet of Things (IoT) devices has pushed for the development of novel transformer-based Anomaly Detection (AD) tools for an accurate monitoring of functionalities in industrial systems. Despite their outstanding performances, transformer models often rely on large...

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Bibliographic Details
Main Authors: Luca Barbieri, Mattia Brambilla, Mario Stefanutti, Ciro Romano, Niccolo De Carlo, Manuel Roveri
Format: Article
Language:English
Published: IEEE 2023-01-01
Series:IEEE Open Journal of Signal Processing
Subjects:
Anomaly detection
machine learning
self-attention
knowledge distillation
Internet of Things
transformer
Online Access:https://ieeexplore.ieee.org/document/10319782/

Internet

https://ieeexplore.ieee.org/document/10319782/

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