Results 41 to 50 of about 266,707 (215)
ISPRS International Journal of Geo-Information, 2021 The extraction of road information from high-resolution remotely-sensed images has important application value in many fields. Rural roads have the characteristics of relatively narrow widths and diversified pavement materials; these characteristics can ...
Hai Tan, Zimo Shen, Jiguang Dai
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Forest/rural road network detection and condition monitoring based on satellite imagery and deep semantic segmentation [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information SciencesSustainable forest and emergency management require comprehensive data on the forest road network and its condition. This paper presents the final framework of the INFOROAD project (https://inforoad.karteco.gr/), which integrates cutting-edge remote ...
D. Kelesakis +8 more
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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
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Fine-Grained Extraction of Road Networks via Joint Learning of Connectivity and Segmentation [PDF]
arXiv, 2023 Road network extraction from satellite images is widely applicated in intelligent traffic management and autonomous driving fields. The high-resolution remote sensing images contain complex road areas and distracted background, which make it a challenge for road extraction. In this study, we present a stacked multitask network for end-to-end segmenting
arxiv
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
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SPIN Road Mapper: Extracting Roads from Aerial Images via Spatial and Interaction Space Graph Reasoning for Autonomous Driving [PDF]
IEEE Conference of Robotics and Automation (ICRA) 2022, 2021 Road extraction is an essential step in building autonomous navigation systems. Detecting road segments is challenging as they are of varying widths, bifurcated throughout the image, and are often occluded by terrain, cloud, or other weather conditions.
arxiv
Road Extraction Assisted by Laser Data [PDF]
Annals of GIS, 2002 Abstract How to make road extraction automatically remains a great challenge up to now. Published researches show that existing approaches are partly available for dealing with shadowed parts of roads especially to rural roads. In this paper, a new approach is proposed to apply laser range data to automatically extract urban roads from digital images ...
Kiyoshi Honda +3 more
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Convolutional Recurrent Network for Road Boundary Extraction [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Creating high definition maps that contain precise information of static elements of the scene is of utmost importance for enabling self driving cars to drive safely. In this paper, we tackle the problem of drivable road boundary extraction from LiDAR and camera imagery.
Raquel Urtasun +4 more
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International Journal of Digital EarthThe extraction of roads from UAV images is challenged by lighting, noise, occlusions, and similar non-road objects, making high-quality road extraction difficult.
Zhen Liu +4 more
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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
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