Automatic recognition and segmentation of architectural elements from 2D drawings by convolutional neural network

Yahan Xiao, Sen Chen, Yasushi Ikeda, Kensuke Hotta

研究成果: Conference contribution

抄録

The BIM modeling process is the most time-consuming aspect. This paper studies the possibility of applying the recognition and segmentation of architectural components by deep learning to assist automatic BIM modeling. The research has two parts: the first one is dataset preparing, that images with the labeled architectural components from an original CAD drawing are made for the network training, and second is training and testing, that a mature network which has been trained in hundreds of labeled images is used to make predictions. The utilization of the current study results is discussed and the optimization method as well.

本文言語English
ホスト出版物のタイトルRE
ホスト出版物のサブタイトルAnthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
編集者Dominik Holzer, Walaiporn Nakapan, Anastasia Globa, Immanuel Koh
出版社The Association for Computer-Aided Architectural Design Research in Asia (CAADRIA)
ページ843-852
ページ数10
ISBN(電子版)9789887891734
出版ステータスPublished - 2020
イベント25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020 - Bangkok, Thailand
継続期間: 2020 8 52020 8 6

出版物シリーズ

名前RE: Anthropocene, Design in the Age of Humans - Proceedings of the 25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
1

Conference

Conference25th International Conference on Computer-Aided Architectural Design Research in Asia, CAADRIA 2020
CountryThailand
CityBangkok
Period20/8/520/8/6

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Building and Construction

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