Large-area, high-resolution characterisation and classification of damage mechanisms in dual-phase steel using deep learning

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: 10.1371/journal.pone.0216493

Event: Veröffentlichung

(where): Aachen

(who): Universitätsbibliothek der RWTH Aachen

(when): 2019

Creator: Kusche, Carl F.
Reclik, Tom
Freund, Martina
Al-Samman, Talal
Kerzel, Ulrich
Korte-Kerzel, Sandra

DOI: 10.18154/RWTH-2019-10367

URN: urn:nbn:de:101:1-2021101806374933334068

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:44 PM CET

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Associated

Kusche, Carl F.
Reclik, Tom
Freund, Martina
Al-Samman, Talal
Kerzel, Ulrich
Korte-Kerzel, Sandra
Universitätsbibliothek der RWTH Aachen

Time of origin

2019

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Large-area, high-resolution characterisation and classification of damage mechanisms in dual-phase steel using deep learning

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Other Objects (12)

Three-dimensional characterisation of deformation-induced damage in dual phase steel using deep learning

Global and High-Resolution Damage Quantification in Dual-Phase Steel Bending Samples with Varying Stress States

On the automated characterisation of inclusion-induced damage in 16MnCrS5 case-hardening steel

SSRM characterisation of FIB induced damage in silicon

High-resolution Radar Based Object Classification for Automotive Applications

Predicting snow damage in conifer forests using a mechanistic snow damage model and high-resolution snow accumulation data

Multiscale investigation of ductile damage in dual phase steels

Characterisation of nanoparticles by means of high-resolution SEM/EDS in transmission mode

Damage Evolution in Nakajima Tests of DP800 Dual Phase Steel

3D Nonlocal Damage Modeling for Steel Structures under Earthquake Loading

Damage Segmentation on High-Resolution Coating Images Using a Novel Two-Stage Network Pipeline

Damage Evolution of High Chromium Steels Utilised for High Temperature Components

Three-dimensional characterisation of deformation-induced damage in dual phase steel using deep learning

Global and High-Resolution Damage Quantification in Dual-Phase Steel Bending Samples with Varying Stress States

On the automated characterisation of inclusion-induced damage in 16MnCrS5 case-hardening steel

SSRM characterisation of FIB induced damage in silicon

High-resolution Radar Based Object Classification for Automotive Applications

Predicting snow damage in conifer forests using a mechanistic snow damage model and high-resolution snow accumulation data

Multiscale investigation of ductile damage in dual phase steels

Characterisation of nanoparticles by means of high-resolution SEM/EDS in transmission mode

Damage Evolution in Nakajima Tests of DP800 Dual Phase Steel

3D Nonlocal Damage Modeling for Steel Structures under Earthquake Loading

Damage Segmentation on High-Resolution Coating Images Using a Novel Two-Stage Network Pipeline

Damage Evolution of High Chromium Steels Utilised for High Temperature Components

Three-dimensional characterisation of deformation-induced damage in dual phase steel using deep learning

Global and High-Resolution Damage Quantification in Dual-Phase Steel Bending Samples with Varying Stress States

On the automated characterisation of inclusion-induced damage in 16MnCrS5 case-hardening steel

SSRM characterisation of FIB induced damage in silicon

High-resolution Radar Based Object Classification for Automotive Applications

Predicting snow damage in conifer forests using a mechanistic snow damage model and high-resolution snow accumulation data

Multiscale investigation of ductile damage in dual phase steels

Characterisation of nanoparticles by means of high-resolution SEM/EDS in transmission mode

Damage Evolution in Nakajima Tests of DP800 Dual Phase Steel

3D Nonlocal Damage Modeling for Steel Structures under Earthquake Loading

Damage Segmentation on High-Resolution Coating Images Using a Novel Two-Stage Network Pipeline

Damage Evolution of High Chromium Steels Utilised for High Temperature Components

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