Dec 9, 2021 · We propose a method that directly infers the final road graph in a single pass. The key idea consists in combining a Fully Convolutional Network in charge of ...
This work proposes a method that directly infers the final road graph in a single pass by combining a Fully Convolutional Network in charge of locating ...
Dec 9, 2021 · The key idea consists in combining a Fully Convolutional Network in charge of locating points of interest such as intersections, dead ends and ...
In this study, we propose an end-to-end road graph extraction framework to detect road centerline keypoints with convolutional neural networks.
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Jul 8, 2024 · Convolutional neural networks (CNN) have made significant advances in detecting roads from satellite images.
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This paper systematically reviews and summarizes the deep-learning-based techniques for automatic road extraction from high-resolution remote sensing images.
We propose RoadTracer, a new method to automatically construct accurate road network maps from aerial images.
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The remote sensing road extraction algorithm primarily uses computer vision technology to perceive the deep features of the road in an image and judge whether ...
Our method is embarrassingly simple in generating road graphs from satellite images using neural networks, that we only need two hyperparameters to filter.
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This research effort proposes a novel method for identifying and extracting roads from aerial images taken after a disaster using graph-based image ...