Bryan Reynolds, Kai Wei, Xiaoyu Liu, Estefany Nunez, Xiaozhou Feng
Our project classifies the artist of a painting and applies image style transfer techniques using convolutional neural networks (CNNs). A dataset containing the works of Vincent van Gogh, Claude Monet, Leonardo da Vinci, Rembrandt, Pablo Picasso, and Salvador Dali was created and cleaned. Five CNN models were trained on the data, resulting in classification accuracy scores ranging from 83-88%. Next, ensemble learning techniques were used to apply a voter algorithm using all five CNN models. The best accuracy score was achieved using a majority voter, which increased the model’s accuracy to ~90%. The style transfer model was created using a software package based on CNN techniques and fine-tuned on one famous painting from each artist.
Two interactive web apps were developed, one for the artist classification model and another for the neural style transfer model: