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Found 6 papers, 3 papers with code
STAD: Spatio-Temporal Adjustment of Traffic-Oblivious Travel-Time Estimation
In this paper, we present STAD, a system that adjusts - on the fly - travel time estimates for any trip request expressed in the form of origin, destination, and departure time.
RoadTagger: Robust Road Attribute Inference with Graph Neural Networks
The usage of graph neural networks allows information propagation on the road network graph and eliminates the receptive field limitation of image classifiers.
Inferring and Improving Street Maps with Data-Driven Automation
Through an evaluation on a large-scale dataset including satellite imagery, GPS trajectories, and ground-truth map data in forty cities, we show that Mapster makes automation practical for map editing, and enables the curation of map datasets that are more complete and up-to-date at less cost.
Machine-Assisted Map Editing
Systems to automatically infer road network graphs from aerial imagery and GPS trajectories have been proposed to improve coverage of road maps.
RoadTracer: Automatic Extraction of Road Networks from Aerial Images
Mapping road networks is currently both expensive and labor-intensive.
Kharita: Robust Map Inference using Graph Spanners
Our algorithms utilize techniques from graph spanners so that they produce maps can effectively handle a wide variety of road and intersection shapes.
Other Computer Science
