Correcting instrumental variation and time-varying drift: A transfer learning approach with autoencoders

IEEE Transactions on Instrumentation and Measurement

Volumn 65, Issue 9, 2016, Pages 2012-2022

  Yan, Ke ^a   Zhang, David ^b,c  

^a TSINGHUA UNIVERSITY   (China)

^b HARBIN INSTITUTE OF TECHNOLOGY   (China)

^c HONG KONG POLYTECHNIC UNIVERSITY   (Hong Kong)

Author keywords

Autoencoder; calibration transfer; drift correction; electronic nose (e nose); spectroscopy; transfer learning

Indexed keywords

ALGORITHMS; FORECASTING; LEARNING SYSTEMS; PATTERN RECOGNITION;

DRIFT CORRECTION; INFLUENTIAL FACTORS; PATTERN RECOGNITION ALGORITHMS; POSTERIOR DISTRIBUTIONS; PREDICTION ALGORITHMS; PREDICTION MODEL; TRANSFER LEARNING; TRANSFER LEARNING METHODS;

ELECTRONIC NOSE;

EID: 84974824084     PISSN: 00189456     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIM.2016.2573078     Document Type: Article

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