Results 41 to 50 of about 2,732,569 (203)

LDANet: A Lightweight Dynamic Addition Network for Rural Road Extraction from Remote Sensing Images

Remote Sensing, 2023
Automatic road extraction from remote sensing images has an important impact on road maintenance and land management. While significant deep-learning-based approaches have been developed in recent years, achieving a suitable trade-off between extraction ...
Bohua Liu, Jianli Ding, Jie Zou, Jinjie Wang, Shuai Huang   +4 more
semanticscholar   +1 more source

A Guided Deep Learning Approach for Joint Road Extraction and Intersection Detection From RS Images and Taxi Trajectories

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Automatic extraction of road information based on data-driven methods is significant for various practical applications. Remote sensing (RS) images and GPS trajectories are two available data sources that can describe roads from a complementary ...
Yali Li, Longgang Xiang, Caili Zhang, Fengwei Jiao, Chenhao Wu   +4 more
doaj   +1 more source

RoadSeg-CD: A Network With Connectivity Array and Direction Map for Road Extraction From SAR Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2022
Road extraction from synthetic aperture radar (SAR) images has attracted much attention in the field of remote sensing image processing. General road extraction algorithms, affected by shadows of buildings and trees, are prone to producing fragmented ...
Fei Gao, Jun Tu, Jun Wang, Amir Hussain, Huiyu Zhou   +4 more
doaj   +1 more source

Bayesian Fusion of Multi-Scale Detectors for Road Extraction from SAR Images

ISPRS International Journal of Geo-Information, 2017
This paper introduces an innovative road network extraction algorithm using synthetic aperture radar (SAR) imagery for improving the accuracy of road extraction.
Rui Xu, Chu He, Xinlong Liu, Dong Chen, Qianqing Qin   +4 more
doaj   +1 more source

Road Extraction From Satellite Images Using Attention-Assisted UNet

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
These days, extracting information from remote sensing data has a great impact on various aspects of our lives, such as infrastructure and urban planning, transportation and traffic management, forecasting and tracking natural disasters, searching for ...
Arezou Akhtarmanesh, D. Abbasi-Moghadam, Alireza Sharifi, Mohsen Hazrati Yadkouri, Aqil Tariq, Linlin Lu   +5 more
semanticscholar   +1 more source

DeepWindow: Sliding Window Based on Deep Learning for Road Extraction From Remote Sensing Images

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2020
The road centerline extraction is the key step of the road network extraction and modeling. The hand-craft feature engineering in the traditional road extraction methods is unstable, which makes the extracted road centerline deviated from the road center
Renbao Lian, Liqin Huang
doaj   +1 more source

A Model-Driven-to-Sample-Driven Method for Rural Road Extraction

Remote Sensing, 2021
Road extraction in rural areas is one of the most fundamental tasks in the practical application of remote sensing. In recent years, sample-driven methods have achieved state-of-the-art performance in road extraction tasks. However, sample-driven methods
Jiguang Dai, Rongchen Ma, Litao Gong, Zimo Shen, Jialin Wu   +4 more
doaj   +1 more source

Semi-Automatic Extraction of Rural Roads under the Constraint of Combined Geometric and Texture Features

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
doaj   +1 more source

Road Extraction using Deep Learning

International Journal of Engineering & Technology, 2018
The Road extraction from aerial image, stands as a quintessential node for the development of rudimentary layers in innumerable fields. From GIS, to Unmanned Aerial vehicles, road maps pave the foundation for data accumulation. This significant process is a result of number of mechanisms devised over the years through iterative experiments and research.
J. D. Dorathi Jayaseeli, D. Malathi, Gopika S   +2 more
openaire   +2 more sources

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 Sciences
Sustainable 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, K. Marthoglou, E. Tokmaktsi, E. Tsiros, A. Karteris, A. Stergiadou, G. Kolkos, P. Daras, N. Grammalidis   +8 more
doaj   +1 more source