Towards deep-learning-based image enhancement for optical camera-based monitoring system of laser powder bed fusion process

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Location: Deutsche Nationalbibliothek Frankfurt am Main

Extent: Online-Ressource

Language: Englisch

Bibliographic citation: In: 10.1080/0951192X.2022.2104461

Event: Veröffentlichung

(where): Aachen

(who): Universitätsbibliothek der RWTH Aachen

(when): 2022

Creator: Zhang, Song
Fu, Tongfang
Jahn, Anne
Collet, Andreas
Schleifenbaum, Johannes Henrich

DOI: 10.18154/RWTH-2022-07654

URN: urn:nbn:de:101:1-2022081301265976593140

Rights: Der Zugriff auf das Objekt ist unbeschränkt möglich.

Last update: 25.03.2025, 1:43 PM CET

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Associated

Zhang, Song
Fu, Tongfang
Jahn, Anne
Collet, Andreas
Schleifenbaum, Johannes Henrich
Universitätsbibliothek der RWTH Aachen

Time of origin

2022

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Towards deep-learning-based image enhancement for optical camera-based monitoring system of laser powder bed fusion process

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Other Objects (12)

Powder-bed stabilization for powder-based additive manufacturing

Optical process monitoring in Laser Powder Bed Fusion using a recoater-based line camera

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Optical process monitoring in Laser Powder Bed Fusion using a recoater-based line camera

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Processability of a hot work tool steel powder mixture in laser-based powder bed fusion

Improved process efficiency in laser-based powder bed fusion of nanoparticle coated maraging tool steel powder

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Nickel-based designed materials manufactured via laser-based powder bed fusion of metals for high-temperature applications

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Enabling cost-based support structure optimization in laser powder bed fusion of metals

Texture-based residual stress analysis of laser powder bed fused Inconel 718 parts

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