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This paper presents a method for estimating the complexity of two-dimensional shapes using Variational Autoencoders (VAEs) and compares it with traditional measures like Fourier analysis and Kolmogorov complexity. The study demonstrates that the proposed method effectively captures various aspects of shape complexity, with results showing strong correlations with human judgments. The authors provide datasets, methods, and results, emphasizing the potential of combining multiple complexity measures for impro

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wasan.3183

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EN