SRMA：用于遥感图像海陆分割的双分支并行多尺度注意力网络

IF 3 3区地球科学 Q2 IMAGING SCIENCE & PHOTOGRAPHIC TECHNOLOGY

International Journal of Remote Sensing Pub Date : 2024-05-07 DOI:10.1080/01431161.2024.2343432

Ye Zhu, Bo Wang, Qi Liu, Shihan Tan, Shengjie Wang, Wenyi Ge

引用次数: 0

摘要

基于深度学习的高分辨率遥感图像海域和陆地分割方法已在环境监测、资源评估、海洋观测等多个领域得到广泛应用。

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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SRMA: a dual-branch parallel multi-scale attention network for remote sensing images sea-land segmentation

The use of deep learning-based high resolution remote sensing image sea and land segmentation method has become prevalent in various fields such as environmental monitoring, resource assessment, an...

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来源期刊

International Journal of Remote Sensing 工程技术-成像科学与照相技术

CiteScore

7.00

自引率

5.90%

发文量

219

审稿时长

4.8 months

期刊介绍： The International Journal of Remote Sensing ( IJRS) is concerned with the theory, science and technology of remote sensing and novel applications of remotely sensed data. The journal’s focus includes remote sensing of the atmosphere, biosphere, cryosphere and the terrestrial earth, as well as human modifications to the earth system. Principal topics include: • Remotely sensed data collection, analysis, interpretation and display. • Surveying from space, air, water and ground platforms. • Imaging and related sensors. • Image processing. • Use of remotely sensed data. • Economic surveys and cost-benefit analyses. • Drones Section: Remote sensing with unmanned aerial systems (UASs, also known as unmanned aerial vehicles (UAVs), or drones).