Digital Media Art Design Model Based on Semantic Guided Bayesian Algorithm

Digital media art design plays an important role in the field of contemporary art, but traditional art design models face the limitations of low accuracy and low stability, and a digital media art design model based on semantically guided Bayesian algorithm provides a potential solution. This study uses a digital media art design model based on semantically guided Bayesian algorithm as the research object. By experimenting and tuning the algorithm, the article evaluates the computational efficiency, stability, and accuracy of the model. The research results show that the computational efficiency of this method is between 83 % and 92%. The digital media art design model based on semantically guided Bayesian algorithm has potential and prospects. It can generate high-quality, expected artistic design works, which can enhance user satisfaction and wide application.