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Publication

METIS-GAN: An approach to generate spatial configurations using deep learning and semantic building models

Hardik Arora; Christoph Langenhan; Frank Petzold; Viktor Eisenstadt; Klaus-Dieter Althoff
In: Proceedings of the European Conference on Product and Process Modeling 2020-2021. European Conference on Product and Process Modeling (ECPPM-2021), May 5-7, Moscow, Russian Federation, European Association of Product and Process Modelling, 2021.

Abstract

In order to recommend architects design options, a system was developed which uses artificial intelligence (AI) methods of case-based reasoning (CBR) and deep learning. Since the system uses deep learning, it requires a sufficient amount of data for training, but currently, not enough amount of semantic building data is available publicly. In this paper, a Generative Adversarial Network (GAN) is considered to generate the semantic building data to train a Deep Neural Network (DNN) to recommend design options.

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