A deep neural network classifies six types of microplastic and natural fibers using 72-dimensional polarization feature vectors from holographic microscopy at 96.7% accuracy, with SHAP analysis showing eigenvalue ratios as the dominant predictors.
Deep classification of microplastics through image fusion techniques,
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2026 1verdicts
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Explainable deep-learning detection of microplastic fibers via polarization-resolved holographic microscopy
A deep neural network classifies six types of microplastic and natural fibers using 72-dimensional polarization feature vectors from holographic microscopy at 96.7% accuracy, with SHAP analysis showing eigenvalue ratios as the dominant predictors.