Forensic application of a novel hybrid neural network

Trace compound identification forms an important element of forensic science. Innovative instrumental designs based on Raman spectroscopy have made possible its in-situ use on fingerprint samples. Recently, the pulse-coupled neural network (PCNN), an oscillatory model neural network, has been used for invariant feature extraction for object recognition and classification. In this paper, we propose a novel hybrid neural network model for quick identification of trace materials from their Raman images. This network consists of a PCNN preprocessor. The features (icons) generated by the PCNN are then fed into a feedforward neural network for classification