  Anime is a storytelling medium similar to movies and books. Anime images are
a kind of artworks, which are almost entirely drawn by hand. Hence, reproducing
existing Anime with larger sizes and higher quality images is expensive.
Therefore, we proposed a model based on convolutional neural networks to
extract outstanding features of images, enlarge those images, and enhance the
quality of Anime images. We trained the model with a training set of 160 images
and a validation set of 20 images. We tested the trained model with a testing
set of 20 images. The experimental results indicated that our model
successfully enhanced the image quality with a larger image-size when compared
with the common existing image enlargement and the original SRCNN method.
