[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 …
Segmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective
MD Hossain, D Chen - ISPRS Journal of Photogrammetry and Remote …, 2019 - Elsevier
Image segmentation is a critical and important step in (GEographic) Object-Based Image
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Analysis (GEOBIA or OBIA). The final feature extraction and classification in OBIA is highly …
Deep learning approaches applied to remote sensing datasets for road extraction: A state-of-the-art review
One of the most challenging research subjects in remote sensing is feature extraction, such
as road features, from remote sensing images. Such an extraction influences multiple …
as road features, from remote sensing images. Such an extraction influences multiple …
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 …
SDUNet: Road extraction via spatial enhanced and densely connected UNet
M Yang, Y Yuan, G Liu - Pattern Recognition, 2022 - Elsevier
Extracting road maps from high-resolution optical remote sensing images has received
much attention recently, especially with the rapid development of deep learning methods …
much attention recently, especially with the rapid development of deep learning methods …
Road extraction from high-resolution remote sensing imagery using deep learning
The road network plays an important role in the modern traffic system; as development
occurs, the road structure changes frequently. Owing to the advancements in the field of high …
occurs, the road structure changes frequently. Owing to the advancements in the field of high …
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 …
RoadNet: Learning to comprehensively analyze road networks in complex urban scenes from high-resolution remotely sensed images
It is a classical task to automatically extract road networks from very high-resolution (VHR)
images in remote sensing. This paper presents a novel method for extracting road networks …
images in remote sensing. This paper presents a novel method for extracting road networks …
Road extraction methods in high-resolution remote sensing images: A comprehensive review
R Lian, W Wang, N Mustafa… - IEEE Journal of Selected …, 2020 - ieeexplore.ieee.org
Road extraction from high-resolution remote sensing images is a challenging but hot
research topic in the past decades. A large number of methods are invented to deal with this …
research topic in the past decades. A large number of methods are invented to deal with this …
Simultaneous road surface and centerline extraction from large-scale remote sensing images using CNN-based segmentation and tracing
Accurate and up-to-date road maps are of great importance in a wide range of applications.
Unfortunately, automatic road extraction from high-resolution remote sensing images …
Unfortunately, automatic road extraction from high-resolution remote sensing images …