Nuclear quadrupole resonance response detection using deep neural networks

作者：

Highlights：

• Nuclear quadrupole resonance detection of prohibited substances.

• Deep learning techniques for signal analysis and detection performance improvement.

• Comparative analysis of several high-performance deep learning solutions.

• Detection accuracy of 99.9% achieved using the AlexNet model.

摘要

•Nuclear quadrupole resonance detection of prohibited substances.•Deep learning techniques for signal analysis and detection performance improvement.•Comparative analysis of several high-performance deep learning solutions.•Detection accuracy of 99.9% achieved using the AlexNet model.

论文关键词：Nuclear quadrupole resonance,Feature set,Deep learning,Comparative analysis,Accuracy,AlexNet

论文评审过程：Received 27 February 2020, Revised 26 March 2021, Accepted 15 May 2021, Available online 24 May 2021, Version of Record 24 May 2021.

论文官网地址：https://doi.org/10.1016/j.eswa.2021.115227