计算机应用与软件2025，Vol.42Issue(6)：186-192,201,8.DOI:10.3969/j.issn.1000-386x.2025.06.024
一种融合注意力机制的轻量级重楼饮片分类方法
A LIGHTWEIGHT PARIS L.DECOCTION PIECES RECOGNITION METHOD BASED ON ATTENTION MECHANISM
摘要
Abstract
Aimed at the automatic recognition of Paris mairei H.Lév.,Paris polyphylla var.yunnanensis(Franch.)Hand.-Mzt.and Paris polyphylla Sm.Var.Alba H Li et R.J.,a lightweight Paris L.decoction pieces classification model based on attention mechanism is proposed.Two multi-scale feature extraction modules were proposed to comprehensively extract multiple scale features.On the basis of ECA-Net and spatial attention mechanism,ECSA-Module(Efficient channel and spatial attention module)was proposed to make full use of feature map channels and spatial information.The backbone network was densely connected,and the random erasing method was used for data enhancement.The experimental results show that the classification accuracy of the model is as high as 96.74％,which is 3.26 percentage points,2.82 percentage points and 2.22 percentage points higher than that of MobileNet-V2,VGG16 and Xception respectively.The recognition system of Paris L.based on this model has high recognition accuracy and high speed,which has important practical application value.关键词
重楼分类/深度学习/卷积神经网络/注意力机制/多尺度特征提取Key words
Paris L.classification/Deep learning/CNN/Attention mechanism/Multi-scale feature extraction分类
信息技术与安全科学引用本文复制引用
罗晋,张俊华,罗旭东,李学芳,张鑫..一种融合注意力机制的轻量级重楼饮片分类方法[J].计算机应用与软件,2025,42(6):186-192,201,8.基金项目
国家自然科学基金项目(62063034,61841112) （62063034,61841112）
云南大学研究生实践创新基金项目(2021Y191). （2021Y191）
