Research on Pneumonia Identification Based on Convolutional Neural Network with Keras
This paper uses TensorFlow as the framework and Keras as the high-level application programming interface and em-ploys convolutional neural network as the training model to design a fast and effective identification system for viral pneumonia.The design primarily uses convolutional neural network to simulate the continuous learning and discrimination process of the human brain,including preprocessing of images,feature extraction,data normalization,model construction,TensorBoard set validation,and graphical display.The pneumonia identification system collects lung CT images,which are fed into the convolu-tional neural network for training after preprocessing.The validation of the validation set leads to the identification of viral pneumonia with an accuracy rate of up to 90％.To further improve detection precision,this paper adjusts the Dropout parame-ter,improves the accuracy of viral pneumonia identification up to about 98％,marking a significant improvement in this meth-od.
万方数据
维普
