Classification For Glucose And Lactose Terahertz Spectra Based On SVM And DNN Methods

Paper (AI1)

Tue, 10 Nov 2020 06:00pm to 06:15pm

Room: Olmstead

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We propose an approach based on support vector machine(SVM) and deep neural networks (DNN) to classify chemical substances under different experimental conditions in terahertz time-domain spectroscopy (THz-TDS). 372 groups of independent signals under different conditions were measured to provide a sufficient training set. 99% accuracy for the SVM and 89.6% for the DNN method are realized in the test set. These excellent classification results show the high potentials in chemical recognition, security detection or clinical diagnosis.

Download Abstract: pid6580205.pdf

Presenters and Authors Info

Presenter: Anonymous

Authors: Li, Kaidi; Chen, Xuequan; MacPherson, Emma Pickwell

The Chinese University of Hong Kong, The Chinese University of Hong Kong, Hong Kong, China, The University of Warwick,United Kingdom&#65307