To improve the accuracy results, you can: 1) increase the number of epochs in the representation learning and the clustering phases; 2) allow the encoder weights to be tuned during the clustering phase; and 3) perform a final fine-tuning step through self-labeling, as described in the original SCAN paper. Note that unsupervised image clustering techniques are not expected to outperform the accuracy of supervised image classification techniques, rather showing that they can learn the semantics of the images and group them into clusters that are similar to their original classes.