Deep learning is the latest trend of machine learning and artificial intelligence research. As a new field of rapid development in the past ten years, more and more researchers pay attention to it. Convolutional neural network (CNN) model is one of the most important classical structures in deep learning model, and its performance has been gradually improved in recent years. Since it can automatically learn the feature representation of sample data, convolutional neural network has been widely used in image classification, object detection, semantic segmentation and natural language processing. This paper first analyzes the model structure of typical convolutional neural network model, which increases the depth and width of the network in order to improve its performance, analyzes the network structure that uses attention mechanism to further improve the performance of the model, and then summarizes and analyzes the current special model structure. Finally, it summarizes and discusses the application of convolutional neural network in related fields, and the future research direction is prospected.
free text keywords: convolutional neural network (cnn) model, feature extraction, computer vision, natural language processing, Electronic computers. Computer science, QA75.5-76.95