Results 1 to 10 of about 175,174 (259)
Road Extraction from High Resolution Remote Sensing Images Based on Vector Field Learning [PDF]
Sensors, 2021 Accurate and up-to-date road network information is very important for the Geographic Information System (GIS) database, traffic management and planning, automatic vehicle navigation, emergency response and urban pollution sources investigation.
Peng Liang +4 more
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Remote Sensing Road Extraction by Road Segmentation Network [PDF]
Applied Sciences, 2021 Road extraction from remote sensing images has attracted much attention in geospatial applications. However, the existing methods do not accurately identify the connectivity of the road. The identification of the road pixels may be interfered with by the
Jiahai Tan, Ming Gao, Kai Yang, Tao Duan
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Multiscale Road Extraction in Remote Sensing Images. [PDF]
Comput Intell Neurosci, 2019 Recent advances in convolutional neural networks (CNNs) have shown impressive results in semantic segmentation. Among the successful CNN-based methods, U-Net has achieved exciting performance. In this paper, we proposed a novel network architecture based on U-Net and atrous spatial pyramid pooling (ASPP) to deal with the road extraction task in the ...
Wulamu A, Shi Z, Zhang D, He Z.
europepmc +4 more sources
Automatic Road Centerline Extraction from Imagery Using Road GPS Data [PDF]
Remote Sensing, 2014 Road centerline extraction from imagery constitutes a key element in numerous geospatial applications, which has been addressed through a variety of approaches.
Chuqing Cao, Ying Sun
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Road Extraction from High-Resolution Remote Sensing Images Based on EDRNet Model [PDF]
Jisuanji gongcheng, 2021 The existing methods for extracting the road parts from high-resolution remote sensing images are limited by the incomplete extraction results and poor boundary quality.To address the problem, a new method based on the EDRNet model is proposed for ...
HE Xiaohui, LI Daidong, LI Panle, HU Shaokai, CHEN Mingyang, TIAN Zhihui, ZHOU Guangsheng
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Remote Sensing, 2023 Road extraction is crucial in urban planning, rescue operations, and military applications. Compared to traditional methods, using deep learning for road extraction from remote sensing images has demonstrated unique advantages.
Xudong Wang +5 more
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Review on Active and Passive Remote Sensing Techniques for Road Extraction
Remote Sensing, 2021 Digital maps of road networks are a vital part of digital cities and intelligent transportation. In this paper, we provide a comprehensive review on road extraction based on various remote sensing data sources, including high-resolution images ...
Jianxin Jia +12 more
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Heliyon, 2023 Photoaging is the main form of external skin aging, and ultraviolet radiation is the main cause. Long-term ultraviolet radiation can cause oxidative stress, inflammation, immune responses, and skin cell apoptosis.
Liping Qu, Feifei Wang, Xiao Ma
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A BOUNDARY AWARE NEURAL NETWORK FOR ROAD EXTRACTION FROM HIGH-RESOLUTION REMOTE SENSING IMAGERY [PDF]
ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2020 Automatic road extraction from high-resolution remote sensing imagery has various applications like urban planning and automatic navigation. Existing methods for automatic road extraction however, focus on regional accuracy but not on the boundary ...
H. Sui, M. Zhou, M. Peng, N. Xiong
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Exploring multiple crowdsourced data to learn deep convolutional neural networks for road extraction
International Journal of Applied Earth Observations and Geoinformation, 2021 Road extraction from high-resolution remote sensing images (HRSIs) is essential for applications in various areas. Although deep convolutional neural networks (DCNNs) have exhibited remarkable success in road extraction, the performance relies on a large
Panle Li +11 more
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