Smart manufacturing under limited and heterogeneous data: a sim-to-real transfer learning with convolutional variational autoencoder in thermoforming

Data in advanced manufacturing are often sparse and collected from various sensory devices in a heterogeneous and multi-modal fashion. Thus, for such intricate input spaces, learning robust and reliable predictive models for product quality assessments entails implementing complex nonlinear models s...

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Veröffentlicht in:	International journal of computer integrated manufacturing Jg. 37; H. 1-2; S. 18 - 36
Hauptverfasser:	Ramezankhani, Milad, Harandi, Mehrtash, Seethaler, Rudolf, Milani, Abbas S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Taylor & Francis 01.02.2024
Schlagworte:	convolutional variational autoencoder Intelligent manufacturing model explainability thermoforming transfer learning
ISSN:	0951-192X, 1362-3052
Online-Zugang:	Volltext
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