卷积神经网络
太赫兹辐射
偏最小二乘回归
太赫兹时域光谱学
模式识别(心理学)
太赫兹光谱与技术
线性判别分析
人工智能
计算机科学
光谱学
数学
物理
光学
机器学习
量子力学
作者
Yao Liu,Hongbin Pu,Qian Li,Da‐Wen Sun
标识
DOI:10.1016/j.saa.2022.122035
摘要
Pericarpium Citri Reticulatae (PCR) in longer storage years possess higher medicinal values, but their differentiation is difficult due to similar morphological characteristics. Therefore, this study investigated the feasibility of using terahertz time-domain spectroscopy (THz-TDS) combined with a convolutional neural network (CNN) to identify PCR samples stored from 1 to 20 years. The absorption coefficient and refractive index spectra in the range of 0.2-1.5 THz were acquired. Partial least squares discriminant analysis, random forest, least squares support vector machines, and CNN were used to establish discriminant models, showing better performance of the CNN model than the others. In addition, the output data points of the CNN intermediate layer were visualized, illustrating gradual changes in these points from overlapping to clear separation. Overall, THz-TDS combined with CNN models could realize rapid identification of different year PCRs, thus providing an efficient alternative method for PCR quality inspection.
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