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Automatic segmentation of 3D synchrotron tomography using trained neural networks

Bugelnig, Katrin and Strohmann, Tobias and Breitbarth, Eric and Requena, Guillermo (2019) Automatic segmentation of 3D synchrotron tomography using trained neural networks. Challenges and Opportunities of Digital Transformation in Fundamental Research with Photons and Neutrons Workshop, 13.-14.6.2019, Hamburg, Deutschland.

Full text not available from this repository.


Item URL in elib:https://elib.dlr.de/130733/
Document Type:Conference or Workshop Item (Poster)
Title:Automatic segmentation of 3D synchrotron tomography using trained neural networks
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Bugelnig, KatrinKatrin.Bugelnig (at) dlr.deUNSPECIFIED
Strohmann, TobiasTobias.Strohmann (at) dlr.deUNSPECIFIED
Breitbarth, EricEric.Breitbarth (at) dlr.dehttps://orcid.org/0000-0002-3479-9143
Requena, GuillermoGuillermo.Requena (at) dlr.deUNSPECIFIED
Date:2019
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Machine Lerning, Deep Learning, Convolutional Neural Networks, Al-Si alloys, 3D connectivity, semantic segmentation
Event Title:Challenges and Opportunities of Digital Transformation in Fundamental Research with Photons and Neutrons Workshop
Event Location:Hamburg, Deutschland
Event Type:Workshop
Event Dates:13.-14.6.2019
Organizer:DESY
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:fixed-wing aircraft
DLR - Research area:Aeronautics
DLR - Program:L AR - Aircraft Research
DLR - Research theme (Project):L - Structures and Materials
Location: Köln-Porz
Institutes and Institutions:Institute of Materials Research > Metallic Structures and Hybrid Material Systems
Deposited By: Bugelnig, Katrin
Deposited On:18 Nov 2019 11:19
Last Modified:18 Nov 2019 11:19

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