Aesthetic Preference

Aesthetic preference research aims to understand and predict how individuals perceive and judge the beauty or appeal of various stimuli, from images and websites to lyrical lines and interior designs. Current research employs machine learning models, including neural networks and fuzzy logic systems, often incorporating linguistic and visual features to predict aesthetic scores and quantify the subjectivity inherent in these judgments. This work is significant for its potential to personalize experiences in fields like image generation, web design, and even artistic creation, by tailoring outputs to individual preferences. Furthermore, the use of explainable AI techniques is improving our understanding of the underlying factors driving aesthetic judgments.