基于深度学习的中草药分类识别

Chinese Herbal Medicine Classification and Recognition Based on Deep Learning

随着国家对中医药发展的大力支持,中草药在治疗某些疾病方面得到了老百姓的认可,取得了很好的效果。应充分利用现代科学技术,推动中药现代化和国际化,以满足时代发展和民众日益增长的医疗保健需求。通过设计基于中草药图像的分类方法,实现对中草药的准确分类,为老百姓普及中医药知识。针对黄河三角洲地区特有的十七种中草药,建立数据集。使用深度学习算法分类,最终提升了分类的准确率,使训练集分离出来的验证集的平均识别准确率达到了96%。

With the country’s strong support for the development of Chinese medicine,Chinese herbal medicine has been recognized by the people in the treatment of certain diseases and achieved good results.We should make full use of modern science and technology to promote the modernization and internationalization of traditional Chinese medicine to meet the development of the times and the growing medical and healthcare needs of the people.By designing the classification method based on the images of Chinese herbal medicine,the accurate classification of Chinese herbal medicine can be achieved and the knowledge of Chinese medicine can be popularized for the common people.For the 17 kinds of Chinese herbal medicines unique to the Yellow River Delta,a data set was established.Using deep learning algorithm for classification,the classification accuracy is finally improved,and the average recognition accuracy of the verification set separated from the training set reaches 96%.