Summary of Deep Learning For Cross-domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook, by Xingchen Zou et al.
Deep Learning for Cross-Domain Data Fusion in Urban Computing: Taxonomy, Advances, and Outlook
by Xingchen Zou, Yibo Yan, Xixuan Hao, Yuehong Hu, Haomin Wen, Erdong Liu, Junbo Zhang, Yong Li, Tianrui Li, Yu Zheng, Yuxuan Liang
First submitted to arxiv on: 29 Feb 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed survey systematically reviews the latest advancements in deep learning-based data fusion methods tailored for urban computing. The paper delves into the role of each modality and data source, categorizes methodology into four primary categories (feature-based, alignment-based, contrast-based, and generation-based), and further categorizes multi-modal urban applications into seven types (urban planning, transportation, economy, public safety, society, environment, and energy). The survey highlights the synergy between deep learning methods and urban computing applications, focusing on the interplay between Large Language Models (LLMs) and urban computing. It postulates future research directions that could revolutionize the field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Urban Computing is a new way to make cities more sustainable by combining data from different sources like maps, traffic cameras, social media, and weather reports. Deep learning methods are helping with this process. This survey looks at the latest advancements in deep learning-based data fusion for Urban Computing. It explores how different types of data and applications work together. The survey also talks about Large Language Models (LLMs) and how they can be used to improve Urban Computing. |
Keywords
* Artificial intelligence * Alignment * Deep learning * Multi modal
