The Convolutional Neural Network Model Based on an Evolutionary Approach For Interactive Picture Book

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.