Research of Convolutional Neural Network on Image Classification

Abstract

With the progress of artificial intelligence, technology based on deep learning is becoming more and more mature, and the application of deep convolutional neural network for image classification has become a popular topic for researchers. The number of the structure of deep convolutional neural network for image classification is keep increasing, and its performance is consistently improving, gradually replace that of traditional methods. According to the process of model development and model optimization, this paper divides the convolutional neural network into two models: classical deep convolutional neural network model and attention mechanism deep convolutional neural network model. The construction methods and characteristics of various kinds of deep convolutional neural network models are comprehensively reviewed, and the performance of various classification models is compared and analyzed. Finally, the problems of deep convolutional neural network model are presented.