Using Reinforcement Learning to Iteratively Construct Road Networks from Satellite Images and GPS Data

Authors

  • Isaiah Gallardo Auburn University

DOI:

https://doi.org/10.1609/aaai.v38i21.30548

Keywords:

Map Inference, Road Network, GPS, Satellite Images

Abstract

Constructing road networks manually is a time consuming and labor-intensive process. This paper proposes a new method to iteratively construct road networks using reinforcement learning from a combined tensor-based representation of satellite image and GPS trajectory data.

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Published

2024-03-24

How to Cite

Gallardo, I. (2024). Using Reinforcement Learning to Iteratively Construct Road Networks from Satellite Images and GPS Data. Proceedings of the AAAI Conference on Artificial Intelligence, 38(21), 23740–23741. https://doi.org/10.1609/aaai.v38i21.30548