Abstract
This article presents the finding of similar cities in Europe from data set Urban Atlas. Basic categories of landuse describe each city. One hundred cites were selected as a basic data set according to size. For finding the similarity, the trained neural network was used. A neural network is part of embedded add-ins Image Analytics in Orange software. One embedder in Orange was selected for the presented purpose. Finally, the hierarchical clustering was used for image descriptors received form neural networks. As a result, the couples of most similar cities is presented in the article. The cities are similar according to the patterns of urban fabrics or green areas patterns or shapes of some areas.
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Acknowledgement
This article has been created with the support of the Operational Program Education for Competitiveness – European Social Fund, project CZ.1.07/2.3.00/20.0170 Ministry of Education, Youth, and Sports of the Czech Republic.
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Dobesova, Z. (2019). The Similarity of European Cities Based on Image Analysis. In: Silhavy, R., Silhavy, P., Prokopova, Z. (eds) Intelligent Systems Applications in Software Engineering. CoMeSySo 2019 2019. Advances in Intelligent Systems and Computing, vol 1046. Springer, Cham. https://doi.org/10.1007/978-3-030-30329-7_31
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DOI: https://doi.org/10.1007/978-3-030-30329-7_31
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