no code implementations • 5 Apr 2021 • Liangrui Pan, Peng Zhang, Chalongrat Daengngam, Mitchai Chongcheawchamnan
This review summarizes the work of Raman spectroscopy in identifying the composition of substances and reviews the preprocessing process of Raman spectroscopy, the analysis methods and applications of artificial intelligence.
no code implementations • 29 Oct 2020 • Liangrui Pan, Pronthep Pipitsunthonsan, Chalongrat Daengngam, Mitchai Chongcheawchamnan
The scheme first transforms the noisy Raman spectrum to a two-dimensional scale map using CWT.
no code implementations • 9 Sep 2020 • Liangrui Pan, Pronthep Pipitsunthonsan, Chalongrat Daengngam, Sittiporn Channumsin, Suwat Sreesawet, Mitchai Chongcheawchamnan
The optimum back-end classifier was obtained by testing the ML and DCNN models with several noisy Raman spectrums (10-30 dB noise power).
no code implementations • 9 Sep 2020 • Liangrui Pan, Pronthep Pipitsunthonsan, Peng Zhang, Chalongrat Daengngam, Apidach Booranawong, Mitcham Chongcheawchamnan
It is shown that output SNR of the proposed noise reduction technology is 10. 24 dB greater than that of the wavelet noise reduction method while the RMSE and the MAPE are 292. 63 and 10. 09, which are much better than the proposed technique.