Results 61 to 70 of about 266,707 (215)
Remote Sensing Image Road Segmentation Method Integrating CNN-Transformer and UNet
IEEE Access, 2023 Real-time and accurate road information is crucial for updating electronic navigation maps. To address the problem of low precision and poor robustness in current semantic segmentation methods for road extraction from remote sensing imagery, we proposed ...
Rui Wang +3 more
doaj +1 more source
PP-LinkNet: Improving Semantic Segmentation of High Resolution Satellite Imagery with Multi-stage Training [PDF]
, 2020 Road network and building footprint extraction is essential for many applications such as updating maps, traffic regulations, city planning, ride-hailing, disaster response \textit{etc}. Mapping road networks is currently both expensive and labor-intensive. Recently, improvements in image segmentation through the application of deep neural networks has
arxiv +1 more source
Accurate Urban Road Centerline Extraction from VHR Imagery via Multiscale Segmentation and Tensor Voting [PDF]
arXiv, 2015 It is very useful and increasingly popular to extract accurate road centerlines from very-high-resolution (VHR) re- mote sensing imagery for various applications, such as road map generation and updating etc. There are three shortcomings of current methods: (a) Due to the noise and occlusions (owing to vehicles and trees), most road extraction methods ...
arxiv
Beyond Road Extraction: A Dataset for Map Update using Aerial Images [PDF]
arXiv, 2021 The increasing availability of satellite and aerial imagery has sparked substantial interest in automatically updating street maps by processing aerial images. Until now, the community has largely focused on road extraction, where road networks are inferred from scratch from an aerial image.
arxiv
Remote Sensing, 2019 The technology used for road extraction from remote sensing images plays an important role in urban planning, traffic management, navigation, and other geographic applications.
Hao He +4 more
doaj +1 more source
Road Region Extraction with Longitudinal Slope
TRANSACTIONS OF THE JAPAN SOCIETY OF MECHANICAL ENGINEERS Series C, 2011 Extraction of road region is a core technology for an autonomous vehicle which achieves safer transport. We propose extraction and modeling method for the road region in front of vehicle, using three-dimensional shape that is analyzed by stereovision.
Naoki Suganuma, Toshiki Matsui
openaire +2 more sources
Extraction of Road Intersections from GPS Traces Based on the Dominant Orientations of Roads [PDF]
ISPRS International Journal of Geo-Information, 2017 Many studies have used Global Navigation Satellite System (GNSS) traces to successfully extract segments of road networks because such data can be rapidly updated at a low cost. However, most studies have not focused on extracting intersections, which are indispensable parts of road networks in terms of connectivity.
Lin Li +5 more
openaire +3 more sources
IEEE Access, 2018 The extraction and vectorization of roads from high spatial resolution remote sensing (HSRRS) images are of great significance to city planning and development.
Zhaoli Hong +4 more
doaj +1 more source
RIRNet: A Direction-Guided Post-Processing Network for Road Information Reasoning
Remote SensingRoad extraction from high-resolution remote sensing images (HRSIs) is one of the tasks in image analysis. Deep convolutional neural networks have become the primary method for road extraction due to their powerful feature representation capability ...
Guoyuan Zhou +6 more
doaj +1 more source
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 +1 more source