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

Internet

http://hdl.handle.net/2286/R.I.53733

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