Spectroscopy and Spectral Analysis, Volume. 41, Issue 1, 94(2021)
Research of Terahertz Time-Domain Spectral Identification Based on Deep Learning
[1] Trofimov V A, Varentsova S A[D]. PLOS ONE, 13, e0201297(2018).
[2] Hu F, Li Z, Liu J et al[D]. Optical and Quantum Electronics, 47, 313(2015).
[3] Mo W, Wang Q, Yin X et al[D]. Advances in Condensed Matter Physics, 2018, 1618750(2018).
[4] Chang T, Guo Q, Liang J et al[D]. Optik, 174, 7(2018).
[5] Tang S, Tong M, Yin M[D]. Analytical Methods, 8, 2794(2016).
[6] Khan S D, Mahmood A, Mumtaz M et al[D]. Applied Spectroscopy, 71, 456(2017).
[8] Naftaly M[D]. IEEE Sensors Journal, 13, 8(2013).
[10] Liu H, Yang Y, Zhang Z et al[D]. Optik, 172, 668(2018).
[11] Jia S, Xu C, Yu S[D]. Neurocomputing, 219, 88(2017).
[12] Charpiat G, Maggiori E, Tarabalka Y et al[D]. IEEE Transactions on Geoscience and Remote Sensing, 55, 645(2017).
[13] Darabi H, Karim F, Majumdar S et al[D]. IEEE Access, 6, 1662(2018).
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Qi-feng HU, Jian CAI. Research of Terahertz Time-Domain Spectral Identification Based on Deep Learning[J]. Spectroscopy and Spectral Analysis, 2021, 41(1): 94
Category: Research Articles
Received: Nov. 15, 2019
Accepted: --
Published Online: Apr. 8, 2021
The Author Email: Qi-feng HU (fengmaomao1991@126.com)