Deconstruct to reconstruct: an automated pipeline for parsing complex CT assemblies

Many technical products are assemblies formed from smaller, versatile building blocks. Deconstructing such assemblies is an industrially important problem and an inspiring challenge for machine learning approaches. For the first time, we present an effective and fully automated pipeline for parsing...

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Veröffentlicht in:	Machine vision and applications Jg. 37; H. 1; S. 8
Hauptverfasser:	Lippmann, Peter, Remme, Roman, Hamprecht, Fred A.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2026 Springer Nature B.V
Schlagworte:	Algorithms Annotations Assemblies Automation Aviation Communications Engineering Computed tomography Computer Science Datasets High resolution Image Processing and Computer Vision Localization Machine learning Medical imaging Networks Pattern Recognition Quality control Segments Complex assemblies 3D Object recognition Assembly reconstruction Computed tomography 3D Segmentation
ISSN:	0932-8092, 1432-1769
Online-Zugang:	Volltext
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