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Design2Struct : Generating website structures from design images using neural networks

Velzel, M.M. (2020) Design2Struct : Generating website structures from design images using neural networks.

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Abstract:The task of translating visual design images into actual websites is a task usually done by human developers, this process can be slow, costly, and takes time away from implementing the actual functionality. In this paper, we address this problem by proposing a novel neural network architecture named Design2Struct. It makes use of Bahdanau Attention in an encoder-decoder structure to generate a sequence describing the website structure in a Domain Specific Language, which can then be compiled to code. The experimental evaluation shows that the proposed method outperforms the state-of-the-art methods by a large margin. Auxiliary, we identify that the existing benchmark dataset is oversimplified, and we propose a new benchmark dataset which is more realistic and one order of magnitude larger than the existing one.
Item Type:Essay (Bachelor)
Faculty:EEMCS: Electrical Engineering, Mathematics and Computer Science
Subject:54 computer science
Programme:Computer Science BSc (56964)
Link to this item:http://purl.utwente.nl/essays/81988
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