Improving the geographical origin classification of <i>Radix glycyrrhizae</i> (licorice) through hyperspectral imaging assisted by U-Net fine structure recognition-Reference-Cited by-同舟云学术

Improving the geographical origin classification of Radix glycyrrhizae (licorice) through hyperspectral imaging assisted by U-Net fine structure recognition

Published:2024 Issue:6 Volume:149 Page:1837-1848
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Zhang Hui¹^ORCID,Pan YiXia¹^ORCID,Chen Yuan¹,Zhang HongXu¹,Xie JianHui¹,Gong XingChu²,Zhu JieQiang¹,Yan JiZhong¹

Affiliation:

1. College of Pharmaceutical Science, Zhejiang University of Technology, No. 18, Chaowang Road, Hangzhou 310014, China

2. Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, 310058, China

Abstract

Collecting hyperspectral data of licorice from different origins, processing the data in three methods, and using multiple classifiers for origin classification, the results showed that the U-Net method could effectively improve the accuracy of origin classification.

Funder

Science and Technology Department of Zhejiang Province

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/AN/D3AN02064A

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