An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network

An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network

The accurate detection of railway tracks is essential for ensuring the safe operation of railways. This study introduces an innovative algorithm that utilizes a graph convolutional network (GCN) and deep neural residual network to enhance feature extraction from high-resolution aerial imagery. The t...

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Bibliographic Details
Main Authors: Yanbin Weng, Meng Xu, Xiahu Chen, Cheng Peng, Hui Xiang, Peixin Xie, Hua Yin
Format: Article
Language:English
Published: MDPI AG 2024-08-01
Series:ISPRS International Journal of Geo-Information
Subjects:
graph convolution
railroad track extraction
residuals
attention mechanism
Online Access:https://www.mdpi.com/2220-9964/13/9/309
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