{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:37:39Z","timestamp":1773247059533,"version":"3.50.1"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:00:00Z","timestamp":1724889600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The National Key Research and Development Program of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"The National Key Research and Development Program of China","award":["52172403"],"award-info":[{"award-number":["52172403"]}]},{"name":"The National Key Research and Development Program of China","award":["62373178"],"award-info":[{"award-number":["62373178"]}]},{"name":"The National Key Research and Development Program of China","award":["22B0577"],"award-info":[{"award-number":["22B0577"]}]},{"name":"The National Key Research and Development Program of China","award":["2024JJ7139"],"award-info":[{"award-number":["2024JJ7139"]}]},{"name":"The National Natural Science Foundation of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"The National Natural Science Foundation of China","award":["52172403"],"award-info":[{"award-number":["52172403"]}]},{"name":"The National Natural Science Foundation of China","award":["62373178"],"award-info":[{"award-number":["62373178"]}]},{"name":"The National Natural Science Foundation of China","award":["22B0577"],"award-info":[{"award-number":["22B0577"]}]},{"name":"The National Natural Science Foundation of China","award":["2024JJ7139"],"award-info":[{"award-number":["2024JJ7139"]}]},{"name":"The project of Hunan Provincial Department of Education of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"The project of Hunan Provincial Department of Education of China","award":["52172403"],"award-info":[{"award-number":["52172403"]}]},{"name":"The project of Hunan Provincial Department of Education of China","award":["62373178"],"award-info":[{"award-number":["62373178"]}]},{"name":"The project of Hunan Provincial Department of Education of China","award":["22B0577"],"award-info":[{"award-number":["22B0577"]}]},{"name":"The project of Hunan Provincial Department of Education of China","award":["2024JJ7139"],"award-info":[{"award-number":["2024JJ7139"]}]},{"name":"Natural Science Foundation of Hunan Province of China","award":["2021YFF0501101"],"award-info":[{"award-number":["2021YFF0501101"]}]},{"name":"Natural Science Foundation of Hunan Province of China","award":["52172403"],"award-info":[{"award-number":["52172403"]}]},{"name":"Natural Science Foundation of Hunan Province of China","award":["62373178"],"award-info":[{"award-number":["62373178"]}]},{"name":"Natural Science Foundation of Hunan Province of China","award":["22B0577"],"award-info":[{"award-number":["22B0577"]}]},{"name":"Natural Science Foundation of Hunan Province of China","award":["2024JJ7139"],"award-info":[{"award-number":["2024JJ7139"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>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 traditional encoder\u2013decoder architecture is expanded with GCN, which improves neighborhood definitions and enables long-range information exchange in a single layer. As a result, complex track features and contextual information are captured more effectively. The deep neural residual network, which incorporates depthwise separable convolution and an inverted bottleneck design, improves the representation of long-distance positional information and addresses occlusion caused by train carriages. The scSE attention mechanism reduces noise and optimizes feature representation. The algorithm was trained and tested on custom and Massachusetts datasets, demonstrating an 89.79% recall rate. This is a 3.17% improvement over the original U-Net model, indicating excellent performance in railway track segmentation. These findings suggest that the proposed algorithm not only excels in railway track segmentation but also offers significant competitive advantages in performance.<\/jats:p>","DOI":"10.3390\/ijgi13090309","type":"journal-article","created":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T11:09:53Z","timestamp":1724929793000},"page":"309","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["An Efficient Algorithm for Extracting Railway Tracks Based on Spatial-Channel Graph Convolutional Network and Deep Neural Residual Network"],"prefix":"10.3390","volume":"13","author":[{"given":"Yanbin","family":"Weng","sequence":"first","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]},{"given":"Meng","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]},{"given":"Xiahu","family":"Chen","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"},{"name":"Zhuzhou Taichang Electronic Information Technology Co., Ltd., Zhuzhou 412007, China"}]},{"given":"Cheng","family":"Peng","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]},{"given":"Hui","family":"Xiang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]},{"given":"Peixin","family":"Xie","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]},{"given":"Hua","family":"Yin","sequence":"additional","affiliation":[{"name":"College of Computer Science, Hunan University of Technology, Tianyuan District, Zhuzhou 412007, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"579","DOI":"10.1016\/j.trpro.2023.02.079","article-title":"Analysis of the Directions of Optimization of the Process of Ensuring Transportation Security in Railway Transport","volume":"68","author":"Shvetsov","year":"2023","journal-title":"Transp. 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