Research and Implementation of CNN Based on TensorFlow
Yu Liang, Binbin Li, Bin Jiao · IOP Conference Series Materials Science and Engineering · 2019
TensorFlow is Google's open source machine learning and deep learning framework, which is convenient and flexible to build the current mainstream deep learning model. Convolutional neural network is a classical model of deep learning, the advantage lies in its powerful feature extraction capabilities of convolutional blocks. Based on the TensorFlow platform, a convolutional neural network model with two-convolution-layers was built. The model was trained and tested with the MNIST data set. The test accuracy rate could reach 99.15%, and compared with the rate of 98.69% with only one-convolution-layer model, which shows that the two-convolution-layers convolutional neural network model has a better ability of feature extraction and classification decision-making.