用于 SAR 图像中船舶探测的场景感知数据增强技术

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

International Journal of Remote Sensing Pub Date : 2024-05-07 DOI:10.1080/01431161.2024.2343433

Yu Tang, Shigang Wang, Jian Wei, Yan Zhao, Jiehua Lin, Jiaqi Yu, Dongliang Li

引用次数: 0

摘要

合成孔径雷达 (SAR) 图像中的船舶探测被广泛应用于海洋监测。近年来，卷积神经网络（CNN）在合成孔径雷达（SAR）船舶探测方面取得了重大进展。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Scene-aware data augmentation for ship detection in SAR images

Ship detection in synthetic aperture radar (SAR) images is widely applied in marine monitoring. In recent years, convolutional neural networks (CNNs) have made significant advances in SAR ship dete...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

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).