[1] J Xiang, M Zhang. Millimeter-Wave radar and its applications(2005).

[2] M T Ghasr, K P Ying, R Zoughi. Wideband millimeter wave interferrometer for high-resolution 3D SAR imaging, 925-929(2015).

[3] F Peng, W Fang, X Wen et al. State of the art and future prospect of the active millimeter wave imaging technique for personnel screening. Journal of Microwaves, 31, 91-96(2015).

[4] Y Zhu, M Yang, L Wu et al. Millimeter-wave holographic imaging algorithm with amplitude corrections. Progress In Electromagnetics Research M, 49, 33-39(2016).

[5] Y Zhu, M Yang, L Wu et al. Practical millimeter-wave holographic imaging system with good robustness. Chinese Optics Letters, 14, 43-47(2016).

[6] S Yeom, D S Lee, J Y Son et al. Concealed object detection using passive millimeter wave imaging(2010).

[7] S Mu, H Shan, J Zhou et al. A method for detecting hidden objects of human body in passive millimeter wave image. Science & Technology Information, 202-203(2014).

[8] F Nian, W Chen, W Wang et al. Concealed objects detection in active millimeter-wave images. Systems Engineering and Electronics, 38, 1462-1469(2016).

[9] J Yao, M Yang, Y Zhu et al. Using convolutional neural network to localize forbidden object in millimeter-wave image. Journal of Infrared and Millimeter Waves, 36, 354-360(2017).

[10] B Zhang, T Chen, B Wang et al. Densely semantic enhancement for domain adaptive region-free detectors. IEEE Transactions on Circuits and Systems for Video Technology(2021).

[11] B Zhang, B Wang, X Wu et al. Domain adaptive detection system for concealed objects using millimeter wave images. Neural Computing and Applications, 33, 11573-11588(2021).

[12] S Luo, X Wu, M Yang et al. Convolutional neural network based human concealed object detection for millimeter wave images. Journal of Fudan University(Natural Science), 57, 442-452(2018).

[13] C Liu, M Yang, X Sun. Towards robust human millimeter wave imaging inspection system in real time with deep learning. Progress In Electromagnetics Research, 161, 87-100(2018).

[14] T Liu, Y Zhao, Y Wei et al. Concealed object detection for Activate millimeter wave image. IEEE Transactions on Industrial Electronics, 66, 9909-9917(2019).

[15] D M Sheen, D L McMakin, T E Hall. Three-dimensional millimeter-wave imaging for concealed weapon detection. IEEE Transactions on microwave theory and techniques, 49, 1581-1592(2001).

[16] Y H Ng, M Hausknecht, S Vijayanarasimhan et al. Beyond short snippets: Deep networks for video classification(2015).

[17] S Hochreiter, J Schmidhuber. Long short-term memory. Neural Computation, 9, 1735-1780(1997).

[18] I Shahzadi, T B Tang, F Meriadeau et al. CNN-LSTM: Cascaded framework for brain tumour classification(2018).

[19] J Redmon, A Farhadi. YOLO9000: Better, Faster, Stronger, 6517-6525(2017).

[20] K Simonyan, A Zisserman. Very deep convolutional networks for large-scale image recognition. Computer Science, arXiv, 1409-1556v6(2014).

[21] M Lin, Q Chen, S Yan. Network In Network. Computer Science, arXiv, 1312.4400(2013).

[22] V Patraucean, A Handa, R Cipolla. Spatio-temporal video autoencoder with differentiable memory. Computer Science, 58, 2415-2422(2015).

[23] W Liu, D Anguelov, D Erhan et al. SSD: Single shot multibox detector. Computer Science, 21-37(2015).

[24] B Zhou, A Khosla, A Lapedriza et al. Learning deep features for discriminative localization, 2921-29(2016).