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Road Extraction by Deep Residual U-Net [PDF]
IEEE Geoscience and Remote Sensing Letters, 2018 Submitted to IEEE Geoscience and Remote Sensing ...
Zhengxin Zhang +2 more
semanticscholar +6 more sources
A review of road extraction from remote sensing images
Journal of Traffic and Transportation Engineering (English ed. Online), 2016 As a significant role for traffic management, city planning, road monitoring, GPS navigation and map updating, the technology of road extraction from a remote sensing (RS) image has been a hot research topic in recent years.
Weixing Wang +5 more
doaj +5 more sources
Road Extraction With Satellite Images and Partial Road Maps [PDF]
IEEE Transactions on Geoscience and Remote Sensing, 2023 This paper has been accepted by IEEE Transactions on Geoscience and Remote ...
Qianxiong Xu +3 more
openaire +5 more sources
A Survey of Deep Learning Road Extraction Algorithms Using High-Resolution Remote Sensing Images. [PDF]
Sensors (Basel)Roads are the fundamental elements of transportation, connecting cities and rural areas, as well as people’s lives and work. They play a significant role in various areas such as map updates, economic development, tourism, and disaster management.
Mo S, Shi Y, Yuan Q, Li M.
europepmc +2 more sources
Dual-Task Network for Road Extraction From High-Resolution Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023 In high-resolution remote sensing images, road scale diversity and occlusions caused by shadows, buildings, and vegetation often pose challenges for road extraction.
Yuzhun Lin +4 more
doaj +2 more sources
RemainNet: Explore Road Extraction from Remote Sensing Image Using Mask Image Modeling
Remote Sensing, 2023 Road extraction from a remote sensing image is a research hotspot due to its broad range of applications. Despite recent advancements, achieving precise road extraction remains challenging.
Zhenghong Li +3 more
doaj +2 more sources
Road Extraction from High Resolution Remote Sensing Images Based on Vector Field Learning [PDF]
Sensors, 2021 Accurate and up-to-date road network information is very important for the Geographic Information System (GIS) database, traffic management and planning, automatic vehicle navigation, emergency response and urban pollution sources investigation.
Peng Liang +4 more
doaj +2 more sources
C-UNet: Complement UNet for Remote Sensing Road Extraction. [PDF]
Sensors (Basel), 2021 Roads are important mode of transportation, which are very convenient for people’s daily work and life. However, it is challenging to accuratly extract road information from a high-resolution remote sensing image.
Hou Y, Liu Z, Zhang T, Li Y.
europepmc +2 more sources
Remote SensingRoad extraction from high-resolution remote sensing images has long been a focal and challenging research topic in the field of computer vision. Accurate extraction of road networks holds extensive practical value in various fields, such as urban ...
Ruyi Liu +7 more
doaj +2 more sources
Multiscale Road Extraction in Remote Sensing Images. [PDF]
Comput Intell Neurosci, 2019 Recent advances in convolutional neural networks (CNNs) have shown impressive results in semantic segmentation. Among the successful CNN-based methods, U-Net has achieved exciting performance. In this paper, we proposed a novel network architecture based on U-Net and atrous spatial pyramid pooling (ASPP) to deal with the road extraction task in the ...
Wulamu A, Shi Z, Zhang D, He Z.
europepmc +5 more sources