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Much of the reference material in Raman spectroscopy is available only as low-quality images in public databases, with no access to the original numerical series, which prevents comparing, measuring peaks and reprocessing the spectra. This work presents RamanScan-PAL2V, a software that reconstructs the (x,y) series from a spectrum image and treats its noise with a filter based on two-value Paraconsistent Annotated Logic (PAL2v), with an adjustable number of Paraconsistent Artificial Neural Cells of Learning (PANCelll), providing students and researchers with previously inaccessible data and a smoothing that preserves the spectrum structure, demonstrated in a practical digitizing and pre-processing case.
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Corrêa et al. (2026) studied this question.
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