[Title]
FTIR absorption spectrum classification using convolutional neural network
[Authors]
박재현, 장희덕, 장동의, 남현우
[Abstract]
FTIR (Fourier transform infrared) equipment measures the infrared absorption spectrum of a chemical contaminant cloud that exists between the light source and spectrometer. The shape of this spectrum is a unique property of a chemical substance. So, by measuring the FTIR spectrum and classifying the material, it is possible to determine the composition of a distant chemical contaminant cloud. In this study, CNN is used for spectral classification of pure chemicals measured by FTIR equipment manufactured by the Agency for Defense Development, and the classification performance of CNN is verified by comparing with other machine learning algorithms.
