Learning visual features from figure-ground maps for urban morphology discovery
Most studies of urban morphology rely on morphometrics, such as building area and street
length. However, these methods often fall short in capturing visual patterns that carry …
length. However, these methods often fall short in capturing visual patterns that carry …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Urban Region Embedding via Multi-View Contrastive Prediction
Recently, learning urban region representations utilizing multi-modal data (information
views) has become increasingly popular, for deep understanding of the distributions of …
views) has become increasingly popular, for deep understanding of the distributions of …
Learning context-aware region similarity with effective spatial normalization over Point-of-Interest data
With the increasing availability of Point-of-Interest (PoI) data driven by the widespread
adoption of location-based services, there is a growing demand to comprehend the …
adoption of location-based services, there is a growing demand to comprehend the …
Urban Region Representation Learning with Attentive Fusion
An increasing number of related urban data sources have brought forth novel opportunities
for learning urban region representations, ie, embeddings. The embeddings describe latent …
for learning urban region representations, ie, embeddings. The embeddings describe latent …
A Survey of Generative Techniques for Spatial-Temporal Data Mining
This paper focuses on the integration of generative techniques into spatial-temporal data
mining, considering the significant growth and diverse nature of spatial-temporal data. With …
mining, considering the significant growth and diverse nature of spatial-temporal data. With …
Regions are Who Walk Them: a Large Pre-trained Spatiotemporal Model Based on Human Mobility for Ubiquitous Urban Sensing
User profiling and region analysis are two tasks of significant commercial value. However, in
practical applications, modeling different features typically involves four main steps: data …
practical applications, modeling different features typically involves four main steps: data …
A Multimodal and Multitask Approach for Adaptive Geospatial Region Embeddings
Geospatial region embeddings are vital in developing predictive models tailored to urban
environments. Such models enable critical applications, including crime rate prediction and …
environments. Such models enable critical applications, including crime rate prediction and …
Mobile Traffic Time Series: Urban Region Representations and Synthetic Generation
G Loddi - 2024 25th IEEE International Conference on Mobile …, 2024 - ieeexplore.ieee.org
The aim of this work is to build a methodology for representing urban regions using service-
specific mobile traffic data from the Netmob dataset. Despite a rich literature on the topic, this …
specific mobile traffic data from the Netmob dataset. Despite a rich literature on the topic, this …