yoshall/Awesome-Multimodal-Urban-Computing

A professional list on Multi-modal Data Fusion Models and Key Datasets for Urban Computing.

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Experimental

This collection helps urban planners, transportation engineers, and public safety analysts understand how different types of city data—like traffic, environmental, and social media information—can be combined to solve complex urban challenges. It takes various urban datasets as input and provides a curated list of advanced deep learning models designed for fusing this multimodal information. The end-user is anyone involved in smart city initiatives, urban development, or research into metropolitan systems.

171 stars. No commits in the last 6 months.

Use this if you are a researcher or practitioner in urban computing looking for a comprehensive overview of cutting-edge deep learning models and datasets that combine diverse city data for applications like urban planning, traffic prediction, or public safety.

Not ideal if you are looking for ready-to-use software or code implementations; this project serves as a research survey and curated list of papers, not a direct software tool.

urban planning transportation engineering public safety smart cities environmental monitoring
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 8 / 25
Community 10 / 25

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Last pushed

Dec 16, 2024

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