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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.

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Considering classroom teaching and online learning as a whole, the activities of teachers and students in the network teaching platform are designed, based on blended learning theory, activity theory and constructivism learning theory. The network teaching platform emphasizes activity and task as its cores, ensuring learning resources and building a learning community. Based on activity theory model, this paper presents a model of learning activity, designs learner activity index and teacher activity index in the platform.

Individuality analyzing of learners is an important research in the network education. However, analyzing learners' individuality is very different at present. The reason is that it is not paid attention to people. They lack of systematic study about it. In the paper, the network learners' individuality model is constructed according to my original research, the features of network learning environment and learner. The network learners' individuality is made up of physical condition, base motivation, psychological traits and social traits. The model is theoretical basis for analyzing learners' individuality in the network education.