Abstract
Recently, the researches of image recognition have been developed remarkably by means of the deep learning. In this study, we focused on the anime storyboards and applied deep convolutional neural networks (DCNNs) to those data. There exists one problem that it takes a lot of effort to tune DCNN hyperparameters. To solve this problem, we propose a novel method called evolutionary the deep learning (evoDL) by means of genetic algorithms (GAs). The effectiveness of evoDL is confirmed by computer simulations taking a real anime storyboard recognition problem as an example.
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Fujino, S., Hatanaka, T., Mori, N., Matsumoto, K. (2018). The Evolutionary Deep Learning based on Deep Convolutional Neural Network for the Anime Storyboard Recognition. In: Omatu, S., RodrÃguez, S., Villarrubia, G., Faria, P., Sitek, P., Prieto, J. (eds) Distributed Computing and Artificial Intelligence, 14th International Conference. DCAI 2017. Advances in Intelligent Systems and Computing, vol 620. Springer, Cham. https://doi.org/10.1007/978-3-319-62410-5_34
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DOI: https://doi.org/10.1007/978-3-319-62410-5_34
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