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Road Extraction From Satellite Imagery by Road Context and Full-Stage Feature
IEEE Geoscience and Remote Sensing Letters, 2023Road extraction from satellite imagery is vital in a broad range of applications. However, extracting complete roads is challenging due to road occlusions caused by the surroundings. This letter proposed an improved encoder–decoder network via extracting
Zhigang Yang +4 more
semanticscholar +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 2022
Road information from high-resolution remote-sensing images is widely used in various fields, and deep-learning-based methods have effectively shown high road-extraction performance.
Gaodian Zhou +4 more
semanticscholar +1 more source
Road information from high-resolution remote-sensing images is widely used in various fields, and deep-learning-based methods have effectively shown high road-extraction performance.
Gaodian Zhou +4 more
semanticscholar +1 more source
IEEE Transactions on Geoscience and Remote Sensing, 2023
Extracting roads from complex high-resolution remote sensing images to update road networks has become a recent research focus. How to apply the contextual spatial correlation and topological structure of the roads properly to improve the extraction ...
L. Dai, Guangyun Zhang, Rongting Zhang
semanticscholar +1 more source
Extracting roads from complex high-resolution remote sensing images to update road networks has become a recent research focus. How to apply the contextual spatial correlation and topological structure of the roads properly to improve the extraction ...
L. Dai, Guangyun Zhang, Rongting Zhang
semanticscholar +1 more source
Road finding for road-network extraction
Proceedings CVPR '88: The Computer Society Conference on Computer Vision and Pattern Recognition, 2003Automatic extraction of roads from aerial photos has been demonstrated in a number of systems, but the systems which display the better capabilities usually rely on manual selection of road starting points. This interaction with a human operator is eliminated by integrating a road-finding module into a road network extraction system.
Z. Aviad, P.D. Carnine
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A Semantics-Geometry Framework for Road Extraction From Remote Sensing Images
IEEE Geoscience and Remote Sensing Letters, 2023Road extraction from remote sensing (RS) images in very high resolution is important for autonomous driving and road planning. Compared with large-scale objects, roads are smaller, winding, and likely to be covered by buildings’ shadows, causing deep ...
Luyi Qiu +3 more
semanticscholar +1 more source
Road Extraction from Satellite Image Via Auxiliary Road Location Prediction
2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2021Road extraction from satellite images is usually corrupted with several disconnected segments so that it does not satisfy the real application. The segmentation-based methods fail to correct separated roads due to the incompleteness information. Therefore, this paper introduces auxiliary Road Location Prediction(RLP), a task leveraging global context ...
Jingtao Hu, Qi Wang, Xuelong Li
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2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2018
Road extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade. In this paper, we propose a semantic segmentation neural network, named D-LinkNet, which adopts encoderdecoder structure, dilated
Lichen Zhou, Chuang Zhang, Ming Wu
semanticscholar +1 more source
Road extraction is a fundamental task in the field of remote sensing which has been a hot research topic in the past decade. In this paper, we propose a semantic segmentation neural network, named D-LinkNet, which adopts encoderdecoder structure, dilated
Lichen Zhou, Chuang Zhang, Ming Wu
semanticscholar +1 more source
Toward Accurate and Efficient Road Extraction by Leveraging the Characteristics of Road Shapes
IEEE Transactions on Geoscience and Remote Sensing, 2023Automatically extracting roads from very high-resolution (VHR) remote sensing images is of great importance in a wide range of remote sensing applications.
Changwei Wang +6 more
semanticscholar +1 more source
Road extraction in suburban areas by region-based road subgraph extraction and evaluation
2009 Joint Urban Remote Sensing Event, 2009In this paper, a road extraction approach for suburban areas from high resolution CIR images is presented. The approach is region-based: the image is first segmented using the normalized cuts algorithm, then the initial segments are grouped to form segments, and road parts are extracted from these segments. Ideally roads in the image correspond to only
Anne Grote +3 more
openaire +1 more source
Road Extraction by Multiscale Deformable Transformer From Remote Sensing Images
IEEE Geoscience and Remote Sensing Letters, 2023Rapid progress has been made in the research of high-resolution remote sensing road extraction tasks in the past years but due to the diversity of road types and the complexity of road context, extracting the perfect road network is still fraught with ...
Peng Hu +5 more
semanticscholar +1 more source