Expert Refined Topic Models to Edit Topic Clusters in Image Analysis Applied to Welding Engineering

This paper proposes a new method to generate edited topics or clusters to analyze images for prioritizing quality issues. The approach is associated with a new way for subject matter experts to edit the cluster definitions by “zapping” or “boosting” pixels. We refer to the information entered by use...

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Bibliografische Detailangaben

Hauptverfasser:	Theodore T. Allen, Hui Xiong, Shih-Hsien Tseng
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2020-06-01
Schriftenreihe:	Informatics
Schlagworte:	Bayesian modeling mixture models Gibbs sampling Latent Dirichlet Allocation
Online-Zugang:	https://www.mdpi.com/2227-9709/7/3/21
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