Work

A TinyML approach to non-repudiable anomaly detection in extreme industrial environments

Year: 2022

Type: conference-paper

Source: IEEE International Workshop on Metrology for Industry 4.0 & IoT (MetroInd4.0&IoT)

DOI: 10.1109/metroind4.0iot54413.2022.9831517

Authors: Mattia Antonini, Miguel Pincheira, Massimo Vecchio, Fabio Antonelli

Institution: Fondazione Bruno Kessler

Language: English

Topic: Anomaly Detection Techniques and Applications

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: closed

Funder: European Commission

OpenAlex ID: W4286572030

FWCI: 2.456

Cites: 13

Cited by: 31

Related to: 10