利用 DeepLab-v3+ 从合成孔径雷达图像自动提取海岸线的方法及其多功能性

IF 1.9 3区工程技术 Q3 ENGINEERING, CIVIL

Coastal Engineering Journal Pub Date : 2024-08-21 DOI:10.1080/21664250.2024.2393528

Lianhui Wu, Sho Ishikawa, Daisuke Inazu, Tsuyoshi Ikeya, Akio Okayasu

引用次数: 0

摘要

本研究利用语义图像分割模型 DeepLab-v3+ 提出了一种从合成孔径雷达（SAR）图像中自动提取海岸线的方法。从光学合成孔径雷达（SAR）图像中提取海岸线的方法是一种基于...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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An automatic shoreline extraction method from SAR imagery using DeepLab-v3+ and its versatility

This study presented an automatic shoreline extraction method from synthetic aperture radar (SAR) imagery using a semantic image segmentation model, DeepLab-v3+. Shorelines extracted from optical s...

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来源期刊

Coastal Engineering Journal 工程技术-工程：大洋

CiteScore

4.60

自引率

8.30%

发文量

审稿时长

7.5 months

期刊介绍： Coastal Engineering Journal is a peer-reviewed medium for the publication of research achievements and engineering practices in the fields of coastal, harbor and offshore engineering. The CEJ editors welcome original papers and comprehensive reviews on waves and currents, sediment motion and morphodynamics, as well as on structures and facilities. Reports on conceptual developments and predictive methods of environmental processes are also published. Topics also include hard and soft technologies related to coastal zone development, shore protection, and prevention or mitigation of coastal disasters. The journal is intended to cover not only fundamental studies on analytical models, numerical computation and laboratory experiments, but also results of field measurements and case studies of real projects.