The Journal of Light Scattering, Volume. 37, Issue 1, 39(2025)

Research on Pathogen Classification Using Raman Spectroscopy Based on Wavelet Transform and Transformer Model

YAO Qi, YANG Jingjing*, and HUANG Ming
Author Affiliations
  • Information Science and Engineering of Yunnan University, Yunnan 650091, China
  • show less
    References(16)

    [1] [1] Cui F Y, Yue Y, Zhang Y, et al. Advancing biosensors with machine learning[J]. ACS sensors, 2020, 5(11): 3346-3364.

    [3] [3] Zhang W, Tang Y, Shi A, et al. Recent developments in spectroscopic techniques for the detection of explosives[J]. Materials, 2018, 11(8): 1364.

    [4] [4] Wang P Y, Chen W G, Wang J X, et al. Hazardous Gas Detection by Cavity-Enhanced Raman Spectroscopy for Environmental Safety Monitoring[J]. Analytical chemistry, 2021, 93(46): 15474-15481.

    [5] [5] Ho C S, Jean N, Hogan C A, et al. Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning[J]. Nature communications, 2019, 10(1): 4927.

    [7] [7] Ralbovsky Nicole M., Lednev Igor K.. Towards development of a novel universal medical diagnostic method: Raman spectroscopy and machine learning[J]. Chemical Society Reviews, 2020, 49(20): 7428-7453.

    [8] [8] Fan X Q, Wang Y, Yu C X, et al. A universal and ac-curate method for easily identifying components in Raman spectroscopy based on deep learning[J]. Analytical Chemistry, 2023, 95(11): 4863-4870.

    [9] [9] Al-Shaebi Z, Uysal Ciloglu F, Nasser M, et al. Highly accurate identification of bacteria's antibioticresistance based on Raman spectroscopy and Unetdeep learning algorithms[J]. ACS omega, 2022, 7(33): 29443-29451.

    [10] [10] Deng L, Zhong Y Z, Wang M N, et al. Scale-adaptive deep model for bacterial Raman spectra identification[J]. IEEE Journal of Biomedical and Health Informatics, 202l, 26(1): 369-378

    [11] [11] Liu B, Liu K X, Qi X Q, et al. Classification of deep-seacold seep bacteria by transformer combined with Raman spectroscopy[J]. Scientific Reports, 2023, 13(1): 3240.

    [12] [12] Fang S Y, Wu S Y, Chen Z, et al. Recent progress and applications of Raman spectrum denoising algorithms in chemical and biological analyses: A review[J]. Trends in Analytical Chemistry, 2024, 172: 117578.

    [13] [13] Yan X A, She D M, Xu Y D. Deep order-wavelet convolutional variational autoencoder for fault identification of rolling bearing under fluctuating speed conditions[J]. Expert Systems with Applications, 2023, 216: 119479.

    [14] [14] Pan L R, Pipitsunthonsan P, Daengngam C, et al. Method for classifying a noisy Raman spectrum-based on a wavelet transform and a deep neural net-work[J]. IEEE Access, 2020, 8: 202716-202727

    [15] [15] Shensa M J. The discrete wavelettrans form: wedding the a trous and Mallat algorithms[J]. IEEE Transactions on signal processing, 1992, 40(10): 2464-2482.

    [16] [16] Mohamed M, Deriche M. An approach for ECGfeature extraction using daubechies4 (DB4) wavelet[J]. International Journal of Computer Applications, 2014, 96(12): 36-41.

    [17] [17] Dosovitskiy A, Beyer L, Kolesnikov A, et al. Animage is worth 16x16 words: Transformers for image recognition at scale. arxiv preprint arxiv: 2010. 11929 (2020).

    [18] [18] Zhou M F, HuY C, Wang R Z, et al. An end-to-enddeep learning approach for Raman spectroscopy classification[J]. Journal of Chemometrics, 2023, 37(2): 3464.

    Tools

    Get Citation

    Copy Citation Text

    YAO Qi, YANG Jingjing, HUANG Ming. Research on Pathogen Classification Using Raman Spectroscopy Based on Wavelet Transform and Transformer Model[J]. The Journal of Light Scattering, 2025, 37(1): 39

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Jul. 25, 2024

    Accepted: Apr. 30, 2025

    Published Online: Apr. 30, 2025

    The Author Email: YANG Jingjing (yangjingjing@ynu.edu.cn)

    DOI:10.13883/j.issn1004-5929.202501006

    Topics