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  5. Automated impact echo spectrum anomaly detection using U-Net Autoencoder

Automated impact echo spectrum anomaly detection using U-Net Autoencoder

Publication date
2024-10
Document type
Konferenzbeitrag
Author
Liebert, Artur  
Dethof, Fabian  
Keßler, Sylvia  
Niggemann, Oliver  
Organisational unit
Informatik im Maschinenbau  
Konstruktionswerkstoffe und Bauwerkserhaltung  
DTEC.bw  
DOI
10.3233/FAIA241058
URI
https://openhsu.ub.hsu-hh.de/handle/10.24405/20414
Conference
27th European Conference on Artificial Intelligence (ECAI 2024) ; Santiago de Compostela, Spain ; October 19–24, 2024
Project
Intelligente Brandgefahrenanalyse für Gebäude und Schutz der Rettungskräfte durch Künstliche Intelligenz und Digitale Brandgebäudezwillinge  
Publisher
IOS Press
Series or journal
Frontiers in Artificial Intelligence and Applications
ISSN
1879-8314
Periodical volume
392
Book title
ECAI 2024
ISBN
978-1-64368-548-9
First page
4634
Last page
4641
Peer-reviewed
✅
Part of the university bibliography
✅
Additional Information
Language
English
Keyword
dtec.bw
Description
This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
Version
Published version
Access right on openHSU
Metadata only access

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