We are presenting a convolutional neural network (CNN) application recognizing the class identity of synthetic cannabinoids based on their Attenuated Total Reflection-Fourier Transform Infrared (ATR-FTIR) spectra. The results indicate that this CNN system can be efficiently used to distinguish JWH synthetic cannabinoids from other substances of forensic interest, but also from other types of synthetic cannabinoids. One of the main advantages of the system is that it can also operate on mobile ATR-FTIR spectrometers used in field operations.

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