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Explosives Detection by Terahertz Spectroscopy and Artificial Neural Network

  • Sijia Li,
  • Meng Chen,
  • Yingxin Wang,
  • Ziran Zhao

摘要

Terahertz spectroscopy can reveal the spectral fingerprint characteristics of different materials in the terahertz range, which allows distinguishing explosives from common materials. In this work, by using the terahertz spectrum as a feature vector to establish an artificial neural network recognition model, we successfully achieve the identification of explosives and conventional materials, as well as the determination of different explosive classes.