现代电子技术2024，Vol.47Issue(3)：29-33,5.DOI:10.16652/j.issn.1004-373x.2024.03.006
基于Xception与迁移学习的中药饮片图像识别研究
Research on traditional Chinese medicine piece image recognition based on Xception and transfer learning
摘要
Abstract
In order to achieve accurate and fast recognition of images of 60 kinds of the traditional Chinese medicine pieces,a dataset of 13 088 images of common traditional Chinese medicine pieces is built,and the transfer learning method is used to train and recognize the images of the traditional Chinese medicine pieces on the basis of the Xception convolutional neural network model in the depth learning algorithm.The initial learning rate for the model training is set as 0.01,the Nesterov momentum hyperparameter in the optimizer is set as 0.9,and the training times are set as 100.The results are obtained as follows.The accuracy of the training set is 100%,the accuracy of the verification set is 97.42%,and the accuracy of the test set is 97.26%.The recognition ability of the model is evaluated and analyzed by combining the confusion matrix.In comparison with the traditional machine learning algorithms that rely on extracting image features of the traditional Chinese medicine pieces,the proposed model has better classification effect and stronger generalization ability.关键词
中药饮片/Xception/迁移学习/深度可分离卷积/混淆矩阵/分类效果Key words
traditional Chinese medicine piece/Xception/transfer learning/depthwise separable convolution/confusion matrix/classification effect分类
信息技术与安全科学引用本文复制引用
张琦,区锦锋,周华英..基于Xception与迁移学习的中药饮片图像识别研究[J].现代电子技术,2024,47(3):29-33,5.基金项目
广东省中医药局科研项目(20221221) （20221221）
2023年广东省科技创新战略专项资金("攀登计划"专项资金)(pdjh2023b0273) （"攀登计划"专项资金）
