Image-based Process Monitoring via Generative Adversarial Autoencoder with Applications to Rolling Defect Detection

Image-based Process Monitoring via Generative Adversarial Autoencoder with Applications to Rolling Defect Detection

abstract: Image-based process monitoring has recently attracted increasing attention due to the advancement of the sensing technologies. However, existing process monitoring methods fail to fully utilize the spatial information of images due to their complex characteristics including the high dimens...

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Bibliographic Details
Other Authors:	YEH, HUAI-MING (Author)
Format:	Dissertation
Language:	English
Published:	2019
Subjects:	Industrial engineering Information technology Computer science adversarial autoencoder anomaly detection generative adversarial networks machine learning statistic unsupervised learning
Online Access:	http://hdl.handle.net/2286/R.I.53733

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