Research on Automatic Recognition Method of Gas Meter Information Based on Convolutional Neural Network
This paper proposes a recognition method based on improved LeNet-5 convolutional neural network.The image infor-mation is collected in real time by adding cameras and communication lines,and the image is processed.The traditional LeNet-5 model is optimized by introducing Gabor filter,ReLU-Softplus function and SVM classifier,and according to the imbalance of image data,the CNN network is optimized by using Grid Loss function,so as to realize the construction of gas meter automatic recognition method.The experimental evaluation under the Caffe deep learning framework shows that the overall recognition accuracy of this method is 99.60％.The total training time of the whole sample set and single code is better than other recogni-tion methods,and the recognition accuracy of incomplete table codes is 99.21％.
gas meter informationautomatic recognitionLeNet-5 modelGrid Loss function
万方数据
维普
