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Enhancing microplastic classification through filter-interfered FTIR spectra using dimensionality reduction and deep learning in low-dimensional spaces
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Enhancing microplastic classification through filter-interfered FTIR spectra using dimensionality reduction and deep learning in low-dimensional spaces
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Researchers developed a method to improve microplastic classification from FTIR spectra that are interfered with by filter backgrounds, using deep learning to extract polymer-specific spectral features even when filter absorption overlaps with plastic signatures, improving accuracy for environmental samples.
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