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Integrating progressive screening strategy-based continuous wavelet transform with EfficientNetV2 for enhanced

Xinyi Liu1, Di Wang2, Rui Wang2

  • 1Zhengzhou Tobacco Research Institute of CNTC, Zhengzhou, 450001, China; Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong, 999077, Hong Kong Special Administrative Region of China.

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|November 23, 2024
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Summary

This study introduces a 2D CWT-EfficientNetV2 model for near-infrared (NIR) spectroscopy. The model accurately quantifies compounds in samples, outperforming existing methods and demonstrating robust performance across datasets.

Keywords:
Continuous wavelet transformEfficientNetV2Feature extractionNear-infrared spectroscopyTwo-dimensional spectrogram

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Chemometrics

Background:

  • Near-infrared (NIR) spectroscopy is increasingly utilized due to portable equipment advancements.
  • Traditional 1D NIR spectra can be enhanced by transforming them into 2D spectrograms using continuous wavelet transform (CWT).

Purpose of the Study:

  • To introduce a high-efficiency 2D CWT-EfficientNetV2 regression model for optimizing NIR spectroscopy applications.
  • To enhance spectral analysis and interpretation through 2D spectrograms.

Main Methods:

  • A novel progressive screening strategy was used to select optimal wavelet functions and scales for CWT.
  • Direct digital mapping (DDM) with a Gray colormap generated 2D spectrograms from wavelet coefficient matrices.
  • The 2D CWT-EfficientNetV2 model was applied for predicting polyphenol content in tobacco leaf samples.

Main Results:

  • The 2D CWT-EfficientNetV2 model demonstrated superior performance compared to partial least squares regression (PLSR) and other models.
  • The model achieved lower root mean square error of prediction (RMSEP) and higher coefficient of determination of prediction (RP2) and RPD on test datasets.
  • Validation on additional public NIR spectral datasets confirmed the model's robustness and reliability.

Conclusions:

  • The 2D CWT-EfficientNetV2 model is a robust and efficient approach for accurate quantification using NIR spectroscopy.
  • This method significantly enhances the analysis and interpretation of spectral information for various target compounds.