Results 11 to 20 of about 2,732,569 (203)
Automatic Road Centerline Extraction from Imagery Using Road GPS Data [PDF]
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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Reconstruction Bias U-Net for Road Extraction From Optical Remote Sensing Images
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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Road Extraction from High-Resolution Remote Sensing Images Based on EDRNet Model [PDF]
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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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
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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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]
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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Road Extraction by Deep Residual U-Net [PDF]
Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network, which combines the strengths of residual learning and U-Net, is proposed for road area
Zhengxin Zhang +2 more
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Exploring multiple crowdsourced data to learn deep convolutional neural networks for road extraction
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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DDU-Net: Dual-Decoder-U-Net for Road Extraction Using High-Resolution Remote Sensing Images [PDF]
Extracting roads from high-resolution remote sensing images (HRSIs) is vital in a wide variety of applications, such as autonomous driving, path planning, and road navigation. Due to the long and thin shape as well as the shades induced by vegetation and
Ying Wang +6 more
semanticscholar +1 more source

