Damage Analysis in Dual-Phase Steel Using Deep Learning: Transfer from Uniaxial to Biaxial Straining Conditions by Image Data Augmentation

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Location: Deutsche Nationalbibliothek Frankfurt am Main

ISSN: 1543-1851

Extent: Online-Ressource

Language: Englisch

Notes: online resource.

Bibliographic citation: Damage Analysis in Dual-Phase Steel Using Deep Learning: Transfer from Uniaxial to Biaxial Straining Conditions by Image Data Augmentation ; day:16 ; month:10 ; year:2020 ; pages:1-11
JOM ; (16.10.2020), 1-11

Creator: Medghalchi, Setareh
Kusche, Carl F.
Karimi, Ehsan
Kerzel, Ulrich
Korte-Kerzel, Sandra

Contributor: SpringerLink (Online service)

DOI: 10.1007/s11837-020-04404-0

URN: urn:nbn:de:101:1-2020113022593982202338

Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 15.08.2025, 7:26 AM CEST

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Medghalchi, Setareh
Kusche, Carl F.
Karimi, Ehsan
Kerzel, Ulrich
Korte-Kerzel, Sandra
SpringerLink (Online service)

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Damage Analysis in Dual-Phase Steel Using Deep Learning: Transfer from Uniaxial to Biaxial Straining Conditions by Image Data Augmentation

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Other Objects (12)

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A unified mesoscopic continuum theory of uniaxial and biaxial liquid crystals

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Experimental investigations of uniaxial and biaxial cold stretching within PC‐films and bars using optical measurements

The formation of biaxial nematic phases in binary mixtures of thermotropic liquid-crystals composed of uniaxial molecules

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Experiments on Low–Cycle Ductile Damage and Failure Under Biaxial Loading Conditions

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A unified mesoscopic continuum theory of uniaxial and biaxial liquid crystals

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The formation of biaxial nematic phases in binary mixtures of thermotropic liquid-crystals composed of uniaxial molecules

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On the Variation of Hardness Due to Uniaxial and Equi-Biaxial Residual Surface Stresses at Elastic–Plastic Indentation

Experiments on Low–Cycle Ductile Damage and Failure Under Biaxial Loading Conditions

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