Results 211 to 220 of about 175,174 (259)
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Road Structure Refined CNN for Road Extraction in Aerial Image
IEEE Geoscience and Remote Sensing Letters, 2017In this letter, we propose a road structure refined convolutional neural network (RSRCNN) approach for road extraction in aerial images. In order to obtain structured output of road extraction, both deconvolutional and fusion layers are designed in the architecture of RSRCNN.
Yanan Wei, Zulin Wang, Mai Xu
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Cascaded Multi-Task Road Extraction Network for Road Surface, Centerline, and Edge Extraction
IEEE Transactions on Geoscience and Remote Sensing, 2022Xiaoyan Lu +6 more
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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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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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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
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Remote Sensing Road Extraction by Refining Road Topology
2020Remote sensing road extraction is one of the research hotspots in high-resolution remote sensing images. However, many road extraction methods cannot hold the edge interference, including shadows of sheltered trees and vehicles. In this paper, a novel remote sensing road extraction (RSRE) method based on deep learning is proposed, which considers the ...
Huiqin Gao, Yuan Yuan, Xiangtao Zheng
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Road extraction for EuroSDR contest
SPIE Proceedings, 2006This paper presents the participation of the SIC to the EuroSDR contest (European Spatial Data Research; formerly known as OEEPE) about road extraction. After presenting the framework of the EuroSDR contest, our approach for road extraction is described.
C. Beumier, V. Lacroix
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Spatial Attention Network for Road Extraction
IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium, 2020Road extraction from high-resolution remote sensing images has become an important method to achieve real-time updating of road network to meet the application requirements. However, due to the diversity of road scenes, various road width, and occlusion, the detected roads in recent researches are often discontinuous and these narrow or fragmented road
Ruonan Chen, Yuan Hu, Tong Wu, Ling Peng
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2005
Abstract : Our research is focused on an investigation of automated road tracking using multiple images, toward a goal of fully automated extraction of 3D road networks with topology and attribution. The use of multiple images for road tracking makes the process more robust, due to analysis of the scene from different view points.
David M. McKeown +2 more
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Abstract : Our research is focused on an investigation of automated road tracking using multiple images, toward a goal of fully automated extraction of 3D road networks with topology and attribution. The use of multiple images for road tracking makes the process more robust, due to analysis of the scene from different view points.
David M. McKeown +2 more
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Context-Supported Road Extraction
1997Contextual information can facilitate automatic extraction of objects from digital imager). This paper addresses the use of context for the automatic extraction of roads from aerial imagery. Context is restricted to knowledge about relations between roads and other objects and is hierarchically structured.
A. Baumgartner +4 more
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