The data-complete and detail-correct road network information serves as important evidence
in numerous transportation-associated applications. Regular and rapid road network …

Abstract The Extraction of Roads from Remote Sensing Imagery is a rapidly developing field
that has significant impacts on both the economic and social domains. In the fields of urban …

Mountain roads are a source of important basic geographic data used in various fields. The
automatic extraction of road images through high-resolution remote sensing imagery using …

The acceleration of urbanization and the increasing demand for precise city planning have
made the extraction of buildings and roads from remote sensing images crucial. Deep …

Road extraction from remote sensing (RS) images in very high resolution is important for
autonomous driving and road planning. Compared with large-scale objects, roads are …

Buildings and roads are the two most basic man-made environments that carry and
interconnect human society. Building and road information has important application value …

Road extraction from high-resolution remote sensing imagery (HRRSI) is a challenging task
due to low spectral variation and the presence of complex background elements, such as …

Urban road extraction is important for the applications of urban planning and transportation.
High-resolution image (HRI) has been one of the most popular data sources for extracting …

In remote sensing images, roads are usually in complex shapes and can be partially
occluded by buildings, trees, and other surroundings. To extract a complete and continuous …

A lane-level intersection map is a cornerstone in high-definition (HD) traffic network maps for
autonomous driving and high-precision intelligent transportation systems applications such …