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 …
The right tools for the job: The case for spatial science tool‐building
G Boeing - Transactions in GIS, 2020 - Wiley Online Library
This article was presented as the 8th annual Transactions in GIS plenary address at the
American Association of Geographers annual meeting in Washington, DC. The spatial …
American Association of Geographers annual meeting in Washington, DC. The spatial …
Multimodal deep learning for robust road attribute detection
Automatic inference of missing road attributes (eg, road type and speed limit) for enriching
digital maps has attracted significant research attention in recent years. A number of …
digital maps has attracted significant research attention in recent years. A number of …
Mining real estate ads and property transactions for building and amenity data acquisition
X Chen, F Biljecki - Urban Informatics, 2022 - Springer
Acquiring spatial data of fine and dynamic urban features such as buildings remains
challenging. This paper brings attention to real estate advertisements and property sales …
challenging. This paper brings attention to real estate advertisements and property sales …
Winning tracker: a new model for real-time winning prediction in MOBA games
With an increasing popularity, Multiplayer Online Battle Arena (MOBA) games where two
opposing teams compete against each other, have played a major role in E-sports …
opposing teams compete against each other, have played a major role in E-sports …
[HTML][HTML] Developing a multi-classifier system to classify OSM tags based on centrality parameters
SH Pazoky, P Pahlavani - … Journal of Applied Earth Observation and …, 2021 - Elsevier
Misclassification of features is a major source of uncertainty in OpenStreetMap (OSM). This
study is an automated data-enrichment study whose primary goal is predicting road classes …
study is an automated data-enrichment study whose primary goal is predicting road classes …
Multimodal fusion of satellite images and crowdsourced GPS traces for robust road attribute detection
Automatic inference of missing road attributes (eg, road type and speed limit) for enriching
digital maps has attracted significant research attention in recent years. A number of …
digital maps has attracted significant research attention in recent years. A number of …
Traj2Former: A Local Context-aware Snapshot and Sequential Dual Fusion Transformer for Trajectory Classification
The wide use of mobile devices has led to a proliferated creation of extensive trajectory data,
rendering trajectory classification increasingly vital and challenging for downstream …
rendering trajectory classification increasingly vital and challenging for downstream …
A context-enriched satellite imagery dataset and an approach for parking lot detection
Automatic detection of geoinformation from satellite images has been a fundamental yet
challenging problem, which aims to reduce the manual effort of human annotators in …
challenging problem, which aims to reduce the manual effort of human annotators in …
Exploiting multi-modal contextual sensing for city-bus's stay location characterization: Towards sub-60 seconds accurate arrival time prediction
Intelligent city transportation systems are one of the core infrastructures of a smart city. The
true ingenuity of such an infrastructure lies in providing the commuters with real-time …
true ingenuity of such an infrastructure lies in providing the commuters with real-time …