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Deep learning-assisted real-time defect detection and process control for electrode manufacturing of lithium-ion battery cells

; ; ; ; ;

In
Machine learning for cyber physical systems : Proceedings of the conference ML4CPS 2025 / Oliver Niggemann, Jürgen Beyerer, Achim Kampker, Rui Yan Li, Görschwin Fey, Alois Kritl, Alexander Diedrich, Christian Kühnert editors, Seiten/Artikel-Nr: 22-33

Konferenz/Event:8. Machine Learning for Cyber-Physical Systems Conference , Berlin , Germany , ML4CPS 2025 , 2025-03-06 - 2025-03-07

Impressum[Hamburg] : [Universitätsbibliothek der HSU]

Umfang22-33

Online
DOI: 10.24405/20022

DOI: 10.18154/RWTH-2025-05712
URL: https://publications.rwth-aachen.de/record/1013802/files/1013802.pdf

Einrichtungen

  1. Lehrstuhl für Production Engineering of E-Mobility Components (420910)


Inhaltliche Beschreibung (Schlagwörter)
Battery cell production (Genormte SW) ; Deep learning (Genormte SW) ; Digitalization (Genormte SW) ; Machine vision (Genormte SW)

OpenAccess:
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Dokumenttyp
Contribution to a conference proceedings

Format
online

Sprache
English

Interne Identnummern
RWTH-2025-05712
Datensatz-ID: 1013802

Beteiligte Länder
Germany

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Related:

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Proceedings  ;  ;  ;  ;  ;  ;  ;
Machine learning for cyber physical systems : Proceedings of the conference ML4CPS 2025
8. Machine Learning for Cyber-Physical Systems Conference, ML4CPS 2025, BerlinBerlin, Germany, 6 Mar 2025 - 7 Mar 20252025-03-062025-03-07 [Hamburg] : [Universitätsbibliothek der HSU] 101 Seiten : Illustrationen, Diagramme () [10.24405/20018]  GO OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS


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420910

 Record created 2025-06-26, last modified 2026-01-22


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