Abstract
BackgroundAttenuated Total Reflectance – Fourier Transform Infrared (ATR-FTIR) spectroscopy and UV–visible microspectrophotometry (MSP) are common in forensic labs. These form a non-destructive method to classify hairs from different individuals using chemometrics. ResultsHair samples were collected from 14 individuals and analyzed. High-level data fusion and neural networks exhibited 100% classification accuracy. SignificanceThe forensic analysis of hair currently involves microscopic and genetic analysis. However, chemical techniques and machine learning can successfully classify hair.
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