Hybrid neural network for the identification of narcotics and explosives

Raman spectroscopy proves to be a versatile technique for forensic tasks. Whilst it is very easy and fast to record a spectrum, it may be very time-consuming for the non-experts (and even the experts) to identify chemicals from the large database of Raman spectra of these materials. Parallel developments in the field of neural networks have come to a stage that they can participate well in the recognition of these materials. In this paper, a novel neural network-based technique is developed and presented for the quick identification of chemical compounds, in particular narcotics and explosives. Preliminary results suggest this hybrid network has a great potential for forensic applications and for recognition of materials, in general.