Baseline Correction and Denoising of Raman Spectra by Deep Residual CNN

Bo-Han Kung; Chiu-Chang Huang; Po-Yuan Hu; Shao-yu Lo; Cheng-Che Lee; Chia-Yu Yao; Chieh-Hsiung Kuan; Chieh-Hsiung Kuan

doi:10.1364/CLEO_AT.2020.JTu2G.28

Conference on Lasers and Electro-Optics
OSA Technical Digest (Optica Publishing Group, 2020),
paper JTu2G.28
•https://doi.org/10.1364/CLEO_AT.2020.JTu2G.28

Baseline Correction and Denoising of Raman Spectra by Deep Residual CNN

Bo-Han Kung, Chiu-Chang Huang, Po-Yuan Hu, Shao-yu Lo, Cheng-Che Lee, Chia-Yu Yao, and Chieh-Hsiung Kuan

CLEO: Science and Innovations 2020

Washington, DC United States
10–15 May 2020
ISBN: 978-1-943580-76-7

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Joint Poster Session 6 (JTu2G)

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B. Kung, C. Huang, P. Hu, S. Lo, C. Lee, C. Yao, and C. Kuan, "Baseline Correction and Denoising of Raman Spectra by Deep Residual CNN," in Conference on Lasers and Electro-Optics, OSA Technical Digest (Optica Publishing Group, 2020), paper JTu2G.28.

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Abstract

A practical deep residual CNN model for the improvement of Raman spectral analysis is proposed in this work. Through the feature transformation in the deep residual blocks, it successfully denoises and precisely corrects the baseline.

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