The impact of architecturally qualified data in deep learning methods for the automatic generation of social housing layouts-Reference-Cited by-同舟云学术

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The impact of architecturally qualified data in deep learning methods for the automatic generation of social housing layouts

Published:2024-02 Issue: Volume:158 Page:105238
ISSN:0926-5805
Container-title:Automation in Construction
language:en
Short-container-title:Automation in Construction

Author:

Carrera Laura,Brullet Nil,Capomaggi Julia,Santacana Amadeu,Devesa Ricardo,Rosselló Guillem,Romero Enrique,Ortega Lluís

Funder

Gobierno de España Ministerio de Ciencia e Innovación

Ministerio de Ciencia e Innovación

Publisher

Elsevier BV

Subject

Building and Construction,Civil and Structural Engineering,Control and Systems Engineering

Reference14 articles.

1. Irregular architectural layout synthesis with graphical inputs;Hua;Autom. Constr.,2016

2. Automated facilities layout: past, present and future;Liggett;Autom. Constr.,2000

3. Constraint-aware interior layout exploration for pre-cast concrete-based buildings;Liu;Vis. Comput.,2013

4. Computer-generated residential building layouts;Merrell;ACM Trans. Graph.,2010

5. Miqp-based layout design for building interiors;Wu,2018

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