Application of Convolutional Neural Networks in Resource Development and Integration of Network Music

The continuous progress of modern information technology has provided abundant learning materials for teachers and students. How to better use and develop such information resources a problem that we must deeply consider now. This article first introduces the basic framework of convolutional neural networks and then applies data mining to the data integration of network music, making network music have a fast search efficiency. Finally, for the feature analysis and evaluation of network music education resources, teachers evaluate and score three students. Then, this article will analyze the Analysis of Database from three aspects. Finally, the indexing and effectiveness of the OM system were demonstrated by comparing this system with two other similar systems. Among them, the success rate of event resolution in this system is higher than that of the other two systems, with the lowest probability reaching 80.2%. Therefore, utilizing convolutional neural networks and resource development and integration is a highly worthy research topic for network music.