Results 1 to 10 of about 179,225 (256)
Remote Sensing, 2021 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.
Zhenfeng Shao +3 more
doaj +3 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
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 +3 more sources
Remote Sensing Road Extraction by Road Segmentation Network [PDF]
Applied Sciences, 2021 Road extraction from remote sensing images has attracted much attention in geospatial applications. However, the existing methods do not accurately identify the connectivity of the road. The identification of the road pixels may be interfered with by the
Jiahai Tan, Ming Gao, Kai Yang, Tao Duan
doaj +2 more sources
Multiscale Road Extraction in Remote Sensing Images [PDF]
Computational Intelligence and Neuroscience, 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 ...
Aziguli Wulamu +3 more
openaire +3 more sources
DeepWindow: Sliding Window Based on Deep Learning for Road Extraction From Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 The road centerline extraction is the key step of the road network extraction and modeling. The hand-craft feature engineering in the traditional road extraction methods is unstable, which makes the extracted road centerline deviated from the road center
Renbao Lian, Liqin Huang
doaj +3 more sources
Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021 Automatic road extraction from remote sensing images plays an important role for navigation, intelligent transportation, and road network update, etc. Convolutional neural network (CNN)-based methods have presented many achievements for road extraction ...
Ziyi Chen +5 more
doaj +3 more sources
Road Extraction by Deep Residual U-Net [PDF]
IEEE Geoscience and Remote Sensing Letters, 2018 Submitted to IEEE Geoscience and Remote Sensing ...
Yunhong Wang +2 more
exaly +3 more sources
Automatic Road Centerline Extraction from Imagery Using Road GPS Data
Remote Sensing, 2014 Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches.
Chuqing Cao, Ying Sun
doaj +3 more sources
JointNet: A Common Neural Network for Road and Building Extraction
Remote Sensing, 2019 Automatic extraction of ground objects is fundamental for many applications of remote sensing. It is valuable to extract different kinds of ground objects effectively by using a general method.
Zhengxin Zhang, Yunhong Wang
doaj +3 more sources