Application of SVM-KNN Network Detection and Virtual Reality in the Visual Design of Artistic Images

Abstract

The birth of computers has brought us unexpected progress and development in many ways. In this very real world of our human existence, the beginning of human perception of the world. It is a sensory organ that collects sensory information, and the same goes for people's artistic creation and design. This paper discusses the classification effect of the combined model of support vector machine and SVM-KNN on the problem of virtual reality art images, analyzes the parameters of the optimized combined model, and then conducts a series of simulation analyses on the optimized model. So using this method can make the collected data more real and reliable, and it will be very convenient for us to process. Use the SVM algorithm to train the classifier when performing data classification and compare different training sample sizes and different kernel functions for empirical analysis and in-depth analysis of the accuracy of the two and the impact of the model. Through the data comparative analysis of SVM-KNN, the obtained results are more real and effective.