Extracting roads from remote sensing images is of significant importance for automatic road
network updating, urban planning, and construction. However, various factors in complex …

Road extraction from high resolution remote sensing (HR-RS) images is an important yet
challenging computer vision task. In this study, we propose an ensemble Wasserstein …

Road extraction from remote sensing imagery is a popular and frontier research focus, since
road information plays an essential role in application fields, such as urban management …

Road network extraction from remote sensing images has played an important role in
various areas. However, due to complex imaging conditions and terrain factors, such as …

Road networks play an important role in navigation and city planning. However, current
methods mainly adopt the supervised strategy that needs paired remote sensing images …

Extracting road information from high-resolution remote sensing images (HRI) can provide
crucial geographic information for many applications. With the improvement of remote …

Extracting roads from complex high-resolution remote sensing images to update road
networks has become a recent research focus. How to apply the contextual spatial …

Road extraction in remote sensing images is of great importance for a wide range of
applications. Because of the complex background, and high density, most of the existing …

Road extraction is a powerful technique support to autonomous driving as it provides
routable road information for motion planning algorithms. High-resolution aerial images offer …

Road extraction from high-resolution remote sensing images is a critical task in image
understanding and analysis, yet it poses significant challenges because of road occlusions …