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- W3120420778 abstract "Abstract We report the potential of U‐Net deep neural network for the efficient removal of noise and background from raw Raman spectra. The U‐Net method was first trained on simulated spectra and then tested with experimental spectra. The quality of the test results was quantified via different signal‐to‐noise ratios and the structural similarity index metric. The U‐Net recovered Raman spectra feature a high structural similarity index, even for raw spectra that were dominated by background. The U‐Net model does not rely on any human intervention." @default.
- W3120420778 created "2021-01-18" @default.
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- W3120420778 date "2021-01-12" @default.
- W3120420778 modified "2023-10-03" @default.
- W3120420778 title "Refinement of spectra using a deep neural network: Fully automated removal of noise and background" @default.
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- W3120420778 doi "https://doi.org/10.1002/jrs.6053" @default.
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