Aiming at the problems of low efficiency and subjectivity in manual recognition of Chinese herbal pieces,this paper proposes an image classification method of Chinese herbal pieces based on transfer learning.Self-built image dataset of Chinese herbal medicine slices,selected MobileNet-V2 model for training,loaded the parameters obtained from the training of ImageNet dataset into the model,modified the number of full connection layer nodes and SoftMax classifier to obtain a new model,frozen the parameters of the full connection layer,and the accura-cy of the new model after training reached 97.67% .The experiments show that the algorithm can accurately classify the images of Chinese herbal pieces,and has less parameters and computation than traditional CNN.It can provide fa-vorable basis for researchers to identify the types of Chinese herbal pieces,and can effectively assist researchers to i-dentify Chinese herbal pieces.
关键词
中药饮片识别/卷积神经网络/迁移学习
Key words
Identification of Chinese herbal pieces/Convolutional neural network/Transfer learning
维普
万方数据