Results 11 to 20 of about 26,498 (203)
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020 Road extraction from the high-resolution remote sensing image is significant for the land planning, vehicle navigation, etc. The existing road extraction methods normally need many preprocessing and subsequent optimization steps.
Qing Guo, Zhipan Wang
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Accurate urban road centerline extraction from VHR imagery via multiscale segmentation and tensor voting [PDF]
Neurocomputing, 2016 Accurate road centerline extraction from very-high-resolution (VHR) remote sensing imagery has various applications, such as road map generation and updating etc. There are three shortcomings of existing methods: (a) due to noise and occlusions, most road extraction methods bring in heterogeneous classification results; (b) morphological thinning is a ...
Guangliang Cheng +4 more
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Island Road Centerline Extraction Based on a Multiscale United Feature
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018 Accurate island road centerlines are important to tourism planning, resource development, and other applications. However, high-resolution island imaging is highly detailed with complex features, which increases the difficulty of road centerline extraction.
Ran Jing +4 more
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A Method for Accurate Road Centerline Extraction From a Classified Image
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014 Accurate road centerline extraction plays an important role in practical remote sensing applications. Most existing centerline extraction methods have many limitations when the classified image contains complicated objects such as curvilinear, close, or short extent features.
Zelang Miao +3 more
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Road Extraction in SAR Images Using Ordinal Regression and Road-Topology Loss
Remote Sensing, 2021 The road extraction task is mainly composed of two subtasks, namely, road detection and road centerline extraction. As the road detection task and road centerline extraction task are strongly correlated, in this paper, we introduce a multitask learning ...
Xiaochen Wei, Xiaolei Lv, Kaiyu Zhang
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Road network extraction using multi-layered filtering and tensor voting from aerial images
Egyptian Journal of Remote Sensing and Space Sciences, 2021 Road network extraction from high-resolution aerial images is a predominant research area in remote sensing due to road network applications in various applications like transportation and industrialization disaster management.
Pramod Kumar Soni +2 more
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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
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International Journal of Applied Earth Observations and Geoinformation, 2023 Although existing research on road intersection detection has been widely conducted using sensor data, mapping grade-separated road intersections in three-dimensions is still lacking.
Xue Yang +5 more
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Remote Sensing, 2022 In this paper, a novel framework for the automatic extraction of road footprints from airborne LiDAR point clouds in urban areas is proposed. The extraction process consisted of three phases: The first phase is to extract road points by using the deep ...
Haichi Ma +4 more
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THE ASSESSMENT OF CURVED CENTERLINE GENERATION IN HDMAPS BASED ON POINT CLOUDS [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Over the decades, autonomous driving technology has attracted a lot of attention and is under rapid development. However, it still suffers from inadequate accuracy in a certain area, such as the urban area, Global Navigation Satellite System (GNSS ...
J. C. Zeng, K. W. Chiang
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