Research and Improvement of Convolutional Neural Network

With the continuous development of Internet technology, there is a growing desire for greater breakthroughs in the field of artificial intelligence to promote social development and progress. However, artificial intelligence has developed slowly in the past due to the complexity of its theory and the constraints of the related software and hardware conditions. As a branch of the field of AI, deep learning can learn the essential features of data and promote the development of AI. Convolution neural network is a typical multi-layer supervised learning neural network, which is widely used in various fields, especially image processing and speech recognition. This paper first introduces the research significance of convolution neural network, and then introduces its structure. The following paper studies and analyzes the architecture of LeNet-5, and improves it. Finally, the Keras framework is used to carry out the experiment on the improved network structure.