Deep convolutional neural networks for Raman spectrum recognition

Love it or loath it, artificial intelligence has revolutionised computer vision and continues to generate great interest in many areas of science. In our 2017 Analyst paper we show that a 1D convolutional neural network is an effective tool for the classification of unknown substances.  Our method, developed for vibrational spectroscopy,  removes the necessity for complicated signal preprocessing  and therefore allows rapid and automated identification of substances. We are currently working with industry to develop this technology further for application in large scale chemical manufacturing.