Urban morphology and artificial intelligence

Pub Date : 2021-11-28 DOI:10.51347/jum.v26i1.4113
Todor Stojanovski
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Abstract

This commentary aims to concisely introduce artificial intelligence and urbantech for urban morphologists. We are in a midst of a new revolution in machine learning with ‘neural nets’ capable of understanding human speech and written language and analysing content on images and videos. The neural nets can semantically parse scenes on images recognizing objects, creating scene graphs, and describing content with text. However, specialized neural nets for urban morphology do not exist. Neural nets can recognise artefacts from specific historical ages or learn about architectural styles only if they are supervised by experts. To create urban morphological architectural intelligence that can help with morphological research or morphologically-informed urban design practices, urban morphologists need to translate their analytics and practices into software specifications. Creating specialized neural nets for urban morphology requires expertise in software engineering and programming effort and seems far in the future, but the International Seminar for Urban Form and Urban Morphology can play a profound role in debating urbantech, needs for intelligent tools and reaching to computational science and technology. Only through coordination and finding synergies the revolution of artificial intelligence will influence urban morphology as urbantech.
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城市形态与人工智能
本文旨在为城市形态学家简要介绍人工智能和城市技术。我们正处于机器学习的一场新革命中,“神经网络”能够理解人类的语音和书面语言,并分析图像和视频中的内容。神经网络可以对图像上的场景进行语义解析,识别对象,创建场景图,并用文本描述内容。然而,用于城市形态的专门神经网络并不存在。只有在专家的监督下,神经网络才能识别特定历史年代的人工制品或了解建筑风格。为了创建有助于形态学研究或形态学知情的城市设计实践的城市形态建筑智能,城市形态学家需要将他们的分析和实践转化为软件规范。为城市形态创建专门的神经网络需要软件工程和编程方面的专业知识,而且似乎还有很长的路要走,但城市形态和城市形态国际研讨会可以在讨论城市技术、智能工具需求和计算科学技术方面发挥深远作用。只有通过协调和寻找协同效应,人工智能的革命才会像城市技术一样影响城市形态。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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