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

摘要

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.