Nov 21, 2018 · Abstract: Road segmentation plays an important role in many applications, such as intelligent transportation system and urban planning.
Road segmentation plays an important role in many applications, such as intelligent transportation system and urban planning. Various road segmentation ...
This study introduces a hybrid network, ICTANet, which incorporate convolutional and Transformer architectures to improve the segmentation performance of fine- ...
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Abstract—Road segmentation plays an important role in many applications, such as intelligent transportation system and urban planning.
Mar 6, 2024 · This paper systematically reviews and summarizes the deep-learning-based techniques for automatic road extraction from high-resolution remote sensing images.
In this paper, a weakly-supervised road segmentation network based on structural and orientational consistency (SOC-RoadNet) is proposed to learn road surface ...
This repository provides an exhaustive overview of deep learning techniques specifically tailored for satellite and aerial image processing.
A DPBFN consists of three parts: a residual multi-scaled dilated convolutional network branch, a transformer branch, and a fusion module. Constructing pyramid ...
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This paper attempts to provide a comprehensive survey on road extraction methods that use 2D earth observing images and 3D LiDAR point clouds.
Deep learning-based semantic segmentation of remote sensing ...
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Semantic segmentation is a fundamental but challenging problem of pixel-level remote sensing (RS) data analysis. Semantic segmentation tasks based on aerial and ...