[HTML][HTML] Road extraction in remote sensing data: A survey
Automated extraction of roads from remotely sensed data come forth various usages ranging
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …
from digital twins for smart cities, intelligent transportation, urban planning, autonomous …
Automatic road detection and centerline extraction via cascaded end-to-end convolutional neural network
Accurate road detection and centerline extraction from very high resolution (VHR) remote
sensing imagery are of central importance in a wide range of applications. Due to the …
sensing imagery are of central importance in a wide range of applications. Due to the …
Road detection and centerline extraction via deep recurrent convolutional neural network U-Net
Road information extraction based on aerial images is a critical task for many applications,
and it has attracted considerable attention from researchers in the field of remote sensing …
and it has attracted considerable attention from researchers in the field of remote sensing …
[HTML][HTML] Building and road detection from remote sensing images based on weights adaptive multi-teacher collaborative distillation using a fused knowledge
Abstract Knowledge distillation is one effective approach to compress deep learning models.
However, the current distillation methods are relatively monotonous. There are still rare …
However, the current distillation methods are relatively monotonous. There are still rare …
BT-RoadNet: A boundary and topologically-aware neural network for road extraction from high-resolution remote sensing imagery
Automatic road extraction from high-resolution remote sensing imagery has various
applications like urban planning and automatic navigation. Existing methods for automatic …
applications like urban planning and automatic navigation. Existing methods for automatic …
Reconstruction bias U-Net for road extraction from optical remote sensing images
Automatic road extraction from remote sensing images plays an important role for
navigation, intelligent transportation, and road network update, etc. Convolutional neural …
navigation, intelligent transportation, and road network update, etc. Convolutional neural …
Spatial information inference net: Road extraction using road-specific contextual information
Deep neural networks perform well in road extraction from very high-resolution satellite
imagery. A network with certain reasoning ability will give more satisfactory road network …
imagery. A network with certain reasoning ability will give more satisfactory road network …
Hierarchical graph-based segmentation for extracting road networks from high-resolution satellite images
Extraction of road networks in urban areas from remotely sensed imagery plays an important
role in many urban applications (eg road navigation, geometric correction of urban remote …
role in many urban applications (eg road navigation, geometric correction of urban remote …
Rngdet: Road network graph detection by transformer in aerial images
Road network graphs provide critical information for autonomous-vehicle applications, such
as drivable areas that can be used for motion planning algorithms. To find road network …
as drivable areas that can be used for motion planning algorithms. To find road network …
Integrated technique of segmentation and classification methods with connected components analysis for road extraction from orthophoto images
Road networks are one of the main urban features. Therefore, road parts extraction from
high-resolution remotely sensed imagery and updated road database are beneficial for …
high-resolution remotely sensed imagery and updated road database are beneficial for …