F Xu, J Zhang, C Gao, J Feng, Y Li - arXiv preprint arXiv:2312.11813, 2023 - arxiv.org
Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the …
Abstract Pre-trained Foundation Models (PFMs) have ushered in a paradigm-shift in Artificial Intelligence, due to their ability to learn general-purpose representations that can be readily …
G White, S Clarke - ECML PKDD 2018 Workshops: Nemesis 2018 …, 2019 - Springer
With the advent of deep learning and new embedded devices capable of running these models at the edge of the network there is potential for deep edges in IoT and smart cities …
The specialization of different urban sectors, theories, and technologies and their confluence in city development have led to a greatly accelerated growth in urban informatics, the …
R Cao, Q Gao, G Qiu - arXiv preprint arXiv:2208.04727, 2022 - arxiv.org
Acceleration of urbanisation is posing great challenges to sustainable development. Growing accessibility to big data and artificial intelligence (AI) technologies have …
D Wang, CT Lu, Y Fu - arXiv preprint arXiv:2304.03892, 2023 - arxiv.org
The two fields of urban planning and artificial intelligence (AI) arose and developed separately. However, there is now cross-pollination and increasing interest in both fields to …
The vitality of urban spaces has been steadily undermined by the pervasive adoption of car- centric forms of urban development as characterised by lower densities, street networks …
Large pre-trained models, also known as foundation models (FMs), are trained in a task- agnostic manner on large-scale data and can be adapted to a wide range of downstream …
In a digitalized era and with the rapid growth of computational skills and advancements, artificial intelligence and Machine Learning uses in various applications are gaining a rising …