Design and Application of Intelligent Processing Technology for Animation Images Based on Deep Learning

The origins of anime can be traced all the way back to the Homo sapiens period of human civilization. Nowadays, anime is a record of life as well as a popular kind of entertainment and a source of ideal trust for many individuals. Children and individuals of all classes and ages enjoy anime. In the opinion of most people, anime is not simply a form of amusement and pleasure, but it can also express deeper meanings, transmit other cultures, and inspire individuals to pursue their aspirations. Image stylistic migration based on convolutional neural networks has developed as a central research path in recent years, and attempts on style migration have evolved as well. However, there are few studies on style migration. In this paper, we propose a deep learning-based solution to the problem of anime-style migration. Experiments on a relevant database show that our proposed method is effective and accurate and has commercial and academic significance.