Research progress on visual image detection based on convolutional neural network

Visual image detection has great research significance and application value in the computer vision field. In recent years, the development of convolutional neural network (CNN) has led to the progress of visual image detection. A large number of new theories and new methods are applied to convolutional neural network, which improves the network feature expression ability, reduces the network complexity and improves the network performance. This paper presents the basic structure of Convolutional CNN, summarizes the improvements of CNN in recent years on different aspects, including convolutional layer, pooling layer, activation function, network regularization and network optimization, sorts various applications of CNN in visual image detection field and summarizes the advantages of CNN in visual image detection field, finally, prospects the future research direction. © 2020, Science Press. All right reserved.