Retrieving genuine nonlinear Raman responses in ultrafast spectroscopy via deep learning
Noise manifests ubiquitously in nonlinear spectroscopy, where multiple sources contribute to experimental signals generating interrelated unwanted components, from random point-wise fluctuations to structured baseline signals. Mitigating strategies are usually heuristic, depending on subjective bias...
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| Autori principali: | , , , , , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
AIP Publishing LLC
2024-06-01
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| Serie: | APL Photonics |
| Accesso online: | http://dx.doi.org/10.1063/5.0198013 |
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