Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …

Automatic extraction of the road surface and road centerline from very high-resolution (VHR)
remote sensing images has always been a challenging task in the field of feature extraction …

Road network extraction is one of the significant assignments for disaster emergency
response, intelligent transportation systems, and real-time updating road network. Road …

Accurate and current road network data is fundamental to land management and emergency
response, yet challenging to produce for unpaved roads in rural and forested regions using …

The detection of objects has become a critical step to update ground cover information, and
the availability of very high-resolution satellite images made us discover new classification …

Road information plays a fundamental role in many applications. However, at present, it is
difficult to extract road information from the traditional nighttime light images in view of their …

Reactive navigation is the most researched navigation technique for underground vehicles.
Local path planning is one of the main research difficulties in reactive navigation. At present …

Road extraction in rural areas is one of the most fundamental tasks in the practical
application of remote sensing. In recent years, sample-driven methods have achieved state …

Roads are an important recognition target in synthetic aperture radar (SAR) image
interpretation. Although a considerable number of high-quality SAR images are now …

For the existence of speckles, many standard optical image processing methods, such as
classification, segmentation, and registration, are restricted to synthetic aperture radar (SAR) …