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Innovative approach improves signal integrity and reduces data acquisition time by 90% in raman spectroscopy.
Raman Spectroscopy In article 10.1002/adom.202500736, Ion Petre and co-workers introduce RADAR, two lightweight deep learning models that simultaneously denoise and correct Raman spectra, reducing data acquisition time by up to 90% while preserving signal integrity. By streamlining artifact removal, RADAR enhances the speed, accuracy, and usability of Raman spectroscopy across diverse applications in materials science, biomedical research, and beyond.
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Sjöberg et al. (2025) studied this question.
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