APPLICATION OF DEEP CONVOLUTION NEURAL NETWORK

Convolution neural network has long been used in the field of digital image processing and speech recognition, and has achieved great success. Before the convolutional neural network was proposed, both image processing and speech recognition were done by traditional machine learning algorithms. Although great results were achieved, it was difficult to make further breakthroughs, so CNN came into being. Currently, CNN for image processing and speech recognition are relatively mature. Both the theoretical research and the industrial application have been very successful, which has promoted CNN's leap-forward development. CNN's success of image processing and speech recognition has stimulated its research frenzy in natural language processing. The current CNN to handle natural language has been widely used, although some achievements have been made, the current effect is not very good. The purpose of this paper is to hopefully give a clearer explanation of the structure of CNN. At the same time, give a brief summary and prospect of current CNN research in image processing, speech recognition and natural language processing.