Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over short distances...

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Navigation Error Characteristics of LIO-, VIO-, and RIMU-Assisted INS/GNSS Multi-Sensor Fusion Schemes in a GNSS-Denied Environment.

Sensors (Basel, Switzerland)·2026
Same author

DRC<sup>2</sup>-Net: A Context-Aware and Geometry-Adaptive Network for Lightweight SAR Ship Detection.

Sensors (Basel, Switzerland)·2025
Same author

CFD Analysis of Particle Dynamics in Accelerated Toroidal Systems for Enhanced PIVG Performance.

Micromachines·2025
查看所有相关文章

相关实验视频

Updated: May 12, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.4K

船舶检测的双模式方法:融合合成孔径雷达和光学卫星图像.

Mahmoud Ahmed1, Naser El-Sheimy2, Henry Leung1

  • 1Department of Electrical and Software Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada.

Sensors (Basel, Switzerland)
|January 25, 2025
PubMed
概括

这项研究引入了一种新的船只检测方法,通过合并合成孔径雷达 (SAR) 和光学卫星图像. 该框架通过结合每个图像类型的专用模型和一种新的融合方法来提高检测准确性.

关键词:
检测变压器的检测变压器多模式融合融合多模式融合合成光圈雷达 (SAR) 是一种合成光圈雷达.

更多相关视频

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.7K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K

相关实验视频

Last Updated: May 12, 2026

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform
06:25

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

8.4K
Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information
10:28

Investigating the Relationship between Sea Surface Chlorophyll and Major Features of the South China Sea with Satellite Information

Published on: June 13, 2020

5.7K
Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy
07:13

Early Detection of Cyanobacterial Blooms and Associated Cyanotoxins using Fast Detection Strategy

Published on: February 25, 2021

3.8K

科学领域:

  • 遥感 遥感 遥感 遥感
  • 计算机视觉 计算机视觉
  • 海事监督部门的监督工作

背景情况:

  • 光学图像提供高分辨率,但受到天气和光线条件的限制.
  • 合成孔径雷达 (SAR) 图像在恶劣条件下表现良好,但受到噪音的影响.
  • 现有的核聚变方法往往无法利用SAR和光学数据的互补优势来进行船舶检测.

研究的目的:

  • 开发一种新的融合框架,用于使用SAR和光学卫星图像来增强船舶检测.
  • 在各种海上场景中提高船舶检测的准确性和处理速度.
  • 有效地整合SAR和光学数据的互补优势.

主要方法:

  • 光学图像检测:使用YOLOv7.7进行对比限度自适应基因图平衡 (CLAHE).
  • SAR图像检测:定制检测变压器 (SAR-EDT) 具有无声化和优化聚合.
  • 融合模块:在欧盟 (IoU) 上交叉,用于界限框重叠,信心分数平均和重复消除.

主要成果:

  • 拟议的框架大大提高了船舶检测的准确性.
  • 在各种海上场景中提高性能,克服单个模式的局限性.
  • 使用CLAHE和YOLOv7.7进行光学图像检测的优化处理速度.

结论:

  • 这种新型的核聚变框架有效地利用互补的SAR和光学数据来实现卓越的船舶检测.
  • 专用模型和强大的融合模块的整合解决了以前方法的局限性.
  • 这项研究通过改进自动化船舶检测来提高海上监视能力.