Evolutionary deep learning based on deep convolutional neural network for anime storyboard recognition

Abstract Recently, image recognition based on deep learning has gained considerable research attention. In this study, we focus on anime storyboards and apply deep convolutional neural networks (DCNNs) to those data. However, it is difficult to tune the DCNN hyperparameters by the gird search method. Therefore, we propose a novel method called evolutionary deep learning (evoDL) by adopting a genetic algorithm (GA) to solve this problem. The effectiveness of evoDL is validated by computer simulations by taking a real anime storyboard recognition problem as an example.