Acoustic scattering signals fed into fine-tuned self-supervised deep learning models classify hair type and moisture at nearly 90% accuracy as a non-invasive alternative to visual methods.
Generalizing auc optimization to multiclass classification for au- dio segmentation with limited training data,
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Acoustic scattering AI for non-invasive object classifications: A case study on hair assessment
Acoustic scattering signals fed into fine-tuned self-supervised deep learning models classify hair type and moisture at nearly 90% accuracy as a non-invasive alternative to visual methods.