@inproceedings{79d776de0e984906b62993267ffa9173,
title = "Target detection and recognition based on active millimeter-wave imaging system",
abstract = "The rapid development of the security inspection system makes the original security inspection equipment gradually unable to meet the needs of the community. The physical characteristics of the millimeter-wave make it more suitable for security imaging systems than X-rays and the active millimeter-wave imaging system has a higher sensitivity and is less affected by the environment than a passive millimeter-wave imaging system. This paper introduces a Ka-band active millimeter-wave imaging system and imaging principle, and uses a new calibration method to correct the images. Finally, the convolutional neural network is used to detect and identify the target.",
keywords = "Active, Component, Convolutional neural network, Ka-band, Millimeter-wave imaging, Target recognition",
author = "Lu Shaobei and Li Shiyong",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2nd IEEE International Conference on Electronics Technology, ICET 2019 ; Conference date: 10-05-2019 Through 13-05-2019",
year = "2019",
month = may,
doi = "10.1109/ELTECH.2019.8839598",
language = "English",
series = "2019 2nd International Conference on Electronics Technology, ICET 2019",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "74--77",
booktitle = "2019 2nd International Conference on Electronics Technology, ICET 2019",
address = "United States",
}