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Research on THz spectrum detection model of stored grain quality based on deep learning
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Paper Abstract

In this work, terahertz time-domain (THz) spectroscopy and deep learning were used to analyze the spectral characteristics of a sample in the terahertz region. Nonlinear dimensionality reduction of the THz spectral data and a detection model for the freshness of stored wheat were investigated by deep learning and THz-TDS. The aim of this work was to enrich and develop the theory and method for testing stored grain quality, and improving the storage of rice through the use of THz technology. Furthermore, the work will provide theoretical basis for reducing the loss of grain storage.

Paper Details

Date Published: 18 December 2019
PDF: 5 pages
Proc. SPIE 11334, AOPC 2019: Optoelectronic Devices and Integration; and Terahertz Technology and Applications, 113341P (18 December 2019); doi: 10.1117/12.2547769
Show Author Affiliations
Hong-yi Ge, Henan Univ. of Technology (China)
Key Lab. of Grain Information Processing and Control, Ministry of Education (China)
Guofang Wu, Henan Univ. of Technology (China)
Yu-ying Jiang, Henan Univ. of Technology (China)
Key Lab. of Grain Information Processing and Control, Ministry of Education (China)
Yuan Zhang, Key Lab. of Grain Information Processing and Control, Ministry of Education (China)
Fei-yu Lian, Key. Lab of Grain Information Processing and Control, Ministry of Education (China)


Published in SPIE Proceedings Vol. 11334:
AOPC 2019: Optoelectronic Devices and Integration; and Terahertz Technology and Applications
Zhiping Zhou; Xiao-Cong Yuan; Daoxin Dai, Editor(s)

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