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In recent years, with the development of computer technology and the Internet, image databases have increased day by day, and the classification of image data has become one of the important research issues for obtaining image information. This article aims to study the role of depth algorithms in network art image classification and print propagation extraction. This article proposes a series of methods of image classification, print dissemination, and deep learning algorithms and also conducts corresponding experiments on the role of deep algorithms in image classification. The experimental results show that the neural network model based on the deep algorithm can effectively identify and classify network images, and its recognition accuracy is more than 80%. The image recognition method based on depth algorithm greatly improves the efficiency of image recognition.

Network Art Image Classification and Print Propagation Extraction Based on Depth Algorithm