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Paper Abstract and Keywords
Presentation
Conversion of floor plan images to graph structures using semantic segmentation
Mantaro Yamada, Toshihiko Yamasaki, Kiyoharu Aizawa (UTokyo)
Abstract (in Japanese) (See Japanese page) 
(in English) In this research, we propose a method that converts floor plan images to graph structures describing rooms’ connection. We use semantic segmentation with deep neural networks for rooms or doors recognition, then construct graph structures based on their connections. These graphs make it easy to compare or evaluate floor plan, and can be applied to a brand-new home search system.
Keyword (in Japanese) (See Japanese page) 
(in English) realty / floor plan image / graph structure / deep learning / FCN / / /  
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Conference Information
Committee HCGSYMPO  
Conference Date 2018-12-12 - 2018-12-14 
Place (in Japanese) (See Japanese page) 
Place (in English) Sinfonia Technology Hibiki Hall Ise 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Human Communication, etc. 
Paper Information
Registration To HCGSYMPO 
Conference Code 2018-12-HCGSYMPO 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Conversion of floor plan images to graph structures using semantic segmentation 
Sub Title (in English)  
Keyword(1) realty  
Keyword(2) floor plan image  
Keyword(3) graph structure  
Keyword(4) deep learning  
Keyword(5) FCN  
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1st Author's Name Mantaro Yamada  
1st Author's Affiliation the University of Tokyo (UTokyo)
2nd Author's Name Toshihiko Yamasaki  
2nd Author's Affiliation the University of Tokyo (UTokyo)
3rd Author's Name Kiyoharu Aizawa  
3rd Author's Affiliation the University of Tokyo (UTokyo)
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