一般觀眾對於｢類神經網路｣之藝術風格轉移認知模式先期研究

In recent years, the use of AI is becoming more mature with the development of neural network technology, and access to various fields including art creation. Meanwhile, it brings new opportunities and challenges in the field of invention, experience, aesthetics and appreciation of art. At present, this field only focuses on the optimization of algorithms, but there are two key points in the improvement of algorithms. (1) As far as technology (rationality) is concerned, can the audience recognize the artistic style transfer through computers? (2) In terms of Art (sensibility), what are the main factors that affect the artistic style transfer through computers? Therefore, the purpose of this paper is to analyze the difference of audience's cognition during the creator's encoding process (color, stroke, texture) and the audience's decoding process (technical level, semantic level, effectiveness level). This study is a series of related studies, in which 31 experts and scholars with a background in art, aesthetics and/or design, were recruited to participate in the previous study to evaluate the degree of fitness and the effect of cognitive between fauvism portraits and corresponding converted images. The results showed that the stylistic characteristics of different images can be recognized and distinguished by subjects. The overall effect of the style transfer will affect the audience's preferences. At last, a research model of artistic style transfer is put forward. The results of the research not only provide suggestions for the optimization of the NST algorithm but also provide some references for the research on the application ofAI into art creation.