Across different instruments about tobacco quantitative analysis model of NIR spectroscopy based on transfer learning

Shen, Huanchao; Geng, Yingrui; Ni, Hongfei; Wang, Hui; Wu, Jizhong; Hao, Xinchang; Tie, Jinxin; Luo, Yi; Xu, Tengfei; Chen, Yong; Liu, Xuesong

doi:10.1039/d2ra05563e

RSC Adv.

2022

DOI: 10.1039/d2ra05563e

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Across different instruments about tobacco quantitative analysis model of NIR spectroscopy based on transfer learning

Huanchao Shen

Yingrui Geng

Hongfei Ni

et al.

Abstract: An instance transfer learning algorithm has been proposed based on weighted ELM to construct NIR quantitative analysis models across different instruments for tobacco.

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When Process Analysis Technology Meets Transfer Learning: A Model Transfer Strategy Between Different Spectrometers for Quantitative Analysis

Yu,

Yao,

Huang

et al. 2024

IEEE Trans. Instrum. Meas.

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When Process Analysis Technology Meets Transfer Learning: A Model Transfer Strategy Between Different Spectrometers for Quantitative Analysis

Yu,

Yao,

Huang

et al. 2024

IEEE Trans. Instrum. Meas.

View full text Add to dashboard Cite

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Across different instruments about tobacco quantitative analysis model of NIR spectroscopy based on transfer learning

Abstract: An instance transfer learning algorithm has been proposed based on weighted ELM to construct NIR quantitative analysis models across different instruments for tobacco.

Cited by 1 publication

References 32 publications

When Process Analysis Technology Meets Transfer Learning: A Model Transfer Strategy Between Different Spectrometers for Quantitative Analysis

When Process Analysis Technology Meets Transfer Learning: A Model Transfer Strategy Between Different Spectrometers for Quantitative Analysis

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