Recognizing the order of four-scene comics by evolutionary deep learning

Abstract

In recent years, comic analysis has become an attractive research topic in the field of artificial intelligence. In this study, we focused on the four-scene comics and applied deep convolutional neural networks (DCNNs) to the data for understanding the order structure. The tuning of the DCNN hyperparameters requires considerable effort. To solve this problem, we propose a novel method called evolutionary deep learning (evoDL) by means of genetic algorithms. The effectiveness of evoDL is confirmed by an experiment conducted to identify structural problems in actual four-scene comics.