世界科学技术-中医药现代化2026，Vol.28Issue(3)：968-977,10.DOI:10.11842/wst.20250318008
基于多尺度卷积网络的药材质量鉴别
Quality Identification of Medicinal Herbs Based on Multi-Scale Convolutional Networks
摘要
Abstract
Objective To address issues in terahertz technology for qualitative and quantitative analysis of medicinal herbs,such as difficulties in standardizing experimental data,indistinct characteristic absorption peaks of medicinal herbs,and the inability of pattern recognition methods to effectively extract spectral features,a quality identification method for medicinal herbs based on a multi-scale convolutional network is proposed.Method Using the terahertz time-domain spectral data of Angelica dahurica,the frequency-domain absorption coefficients are first obtained through fast Fourier transform(FFT)and converted into two-dimensional images.The InceptionTime network is then employed to extract multi-scale features from the time-domain waveforms,while the ConvNeXt network extracts texture features from the frequency-domain images.The outputs from the two branches are fixed-length feature vectors,which are concatenated at the channel level and fed into a fully connected fusion network.Finally,the Softmax function is applied to generate the probability distribution of quality categories,forming the QID-MCN model for comprehensive analysis of medicinal herbs.Results The QID-MCN model achieved an identification accuracy of 98.6%for Angelica dahurica,significantly improving the accuracy and speed of medicinal herb quality identification.Conclusion The QID-MCN model effectively solves the challenge of extracting terahertz spectral features by parallel extraction and integration of time-domain and frequency-domain features,providing an efficient and precise method for medicinal herb quality analysis.关键词
中药材质量鉴定/太赫兹技术/深度学习/卷积网络Key words
Quality identification of Chinese medicinal materials/Terahertz technology/Deep learning/Convolutional network分类
医药卫生引用本文复制引用
夏涵,高攀,朱嘉静,张云,周俊,张宁,刘勇国..基于多尺度卷积网络的药材质量鉴别[J].世界科学技术-中医药现代化,2026,28(3):968-977,10.基金项目
四川省科学技术厅四川省重点研发计划(2023YFS0338):基于信息融合的川产道地药材"老药工智能决策系统"研发与应用,负责人:刘勇国 （2023YFS0338）
四川省科学技术厅四川省区域创新合作项目(2023YFQ0010):川渝特色院内制剂研发与多向转化,负责人:张宁 （2023YFQ0010）
四川省科学技术厅四川省应用基础研究(2020YJ0369):基于白芷科学熏硫工艺的二氧化硫限量快速检测技术研究,负责人:周俊. （2020YJ0369）
