Developing a Conditional Variational Autoencoder to Guide Spectral Data Augmentation for Calibration Modeling

To deal with the typically insufficiently labeled samples involved in practical spectroscopy measurements, a conditional variational autoencoder (CVAE) is proposed to guide the spectral data augmentation calibration modeling method for in situ measurement. First, the CVAE is designed to generate the...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement Jg. 71; S. 1 - 8
Hauptverfasser:	Mu, Guoqing, Chen, Junghui
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2022 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Calibration Calibration model building conditional variational autoencoder (CVAE) Data augmentation Data models Fermentation In situ measurement Numerical models Regression models semi-supervised Semi-supervised learning Semisupervised learning Spectra Spectroscopy Spectrum analysis Task analysis Training virtual sample
ISSN:	0018-9456, 1557-9662
Online-Zugang:	Volltext
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