Identification of amino acids in a mixture based on a CNN

Bo Wang; Tian Song; Kun Meng; Zeren Li; Liguo Zhu

doi:10.1117/12.2606132

9 September 2021 Identification of amino acids in a mixture based on a CNN

Bo Wang, Tian Song, Kun Meng, Zeren Li, Liguo Zhu

Proceedings Volume 11909, Tenth International Symposium on Ultrafast Phenomena and Terahertz Waves (ISUPTW 2021); 1190910 (2021) https://doi.org/10.1117/12.2606132
Event: Tenth International Symposium on Ultrafast Phenomena and Terahertz Waves (ISUPTW 2021), 2021, Chengdu, China

Abstract

THz-TDS systems are widely used in non-destructive inspection and chemical inspection and are receiving increasing recognition due to its wide spectrum and the ability to distinguish isomers that can not be easily identified by other types of spectrum. Convolutional neural network is the state-of-the-art technique for feature extraction and classification of single-dimensional and multidimensional matrices and is applicable to identify the THz absorption spectrum of chemicals. We present a method based on a CNN to identify the THz absorption spectrum of several types of amino acids measured by transmission spectroscopy of a THz-TDS system and receive a rate of accuracy close to 100% even for isomers such as L-Tyrosine and DL-Tyrosine. We also present the initial results of quantitatively identifying the amino acids in a mixture, which is among the first outcomes of such research. This technology will support the future application of THz-TDS in drug detection under complex states and environments.

Citation Download Citation

Bo Wang, Tian Song, Kun Meng, Zeren Li, and Liguo Zhu "Identification of amino acids in a mixture based on a CNN", Proc. SPIE 11909, Tenth International Symposium on Ultrafast Phenomena and Terahertz Waves (ISUPTW 2021), 1190910 (9 September 2021); https://doi.org/10.1117/12.2606132

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