@inproceedings{d6700bd9c98541e3bcb1826bd9513087,
title = "Towards a Robust Evaluation Framework for Generative Urban Design",
abstract = "Thispaper critically reviews the evaluation methods employed in the Generative Urban Design (GUD) literature. The review reveals various evaluation methods, including human-based, performance-based, and statistical evaluation· An analysis of the evaluation methods shows that each approach has limitations, and none fully addresses the unique challenges of evaluating GUD. The paper concludes that more robust and comprehensive evaluation methods are neededfor GUD.",
keywords = "DeepLeammg，GAN, FID score, Generative Urban Design, Machine-Learning",
author = "Haya Brama and Agata Dalach and Tal Grinshpoun and Jonathan Dortheimer",
note = "Publisher Copyright: {\textcopyright} 2024, Education and research in Computer Aided Architectural Design in Europe. All rights reserved.; 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2024 ; Conference date: 09-09-2024 Through 13-09-2024",
year = "2024",
doi = "https://doi.org/10.52842/conf.ecaade.2024.1.529",
language = "الإنجليزيّة",
isbn = "9789491207372",
series = "Proceedings of the International Conference on Education and Research in Computer Aided Architectural Design in Europe",
publisher = "Education and research in Computer Aided Architectural Design in Europe",
pages = "529--538",
editor = "Odysseas Kontovourkis and Phocas, {Marios C.} and Gabriel Wurzer",
booktitle = "Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe, eCAADe 2024",
}