Abstract
Creating interactive picture books based on human “Kansei” is one of the most interesting and difficult issues in the artificial intelligence field. We have proposed a novel interactive picture book based on Pictgent (Picture Information Shared Conversation Agent) and CASOOK (Creative Animating Sketchbook). Since our system accepts human sketches instead of natural languages, a high degree of sketch recognition accuracy is required. Recently, convolutional neural networks (CNNs) have been applied to various image- recognition tasks successfully. We have also adopted a CNN model for the sketch recognition of the proposed interactive picture book. However, it takes a considerable effort to tune the hyperparameters of a CNN. In this paper, we propose a novel parameter tuning method for CNNs using an evolutionary approach. The effectiveness of the proposed method is confirmed by a computer simulation that uses, as an example, a scribble-object recognition problem for the interactive picture book.
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Acknowledgments
A part of this work was supported by JSPS KAKENHI Grant, Grant-in-Aid for Scientific Research (C), 26330282. A part of this work was also supported by JSPS KAKENHI Grant, Grant-in-Aid for JSPS Fellows, 16J10941.
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Fujino, S., Hasegawa, T., Ueno, M., Mori, N., Matsumoto, K. (2017). The Convolutional Neural Network Model Based on an Evolutionary Approach For Interactive Picture Book. In: Leu, G., Singh, H., Elsayed, S. (eds) Intelligent and Evolutionary Systems. Proceedings in Adaptation, Learning and Optimization, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-49049-6_8
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DOI: https://doi.org/10.1007/978-3-319-49049-6_8
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