Progress of research on deep learning algorithms for object detection in optical remote sensing images

Reviews | Views:4802Downloads:15732CSCD:20

Export
Share
Collection
Album

Progress of research on deep learning algorithms for object detection in optical remote sensing images
- role：First author第一作者
- Affiliation：
  College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
- Email：xudanqing@nuaa.edu.cn
- Introduction：徐丹青，研究方向为遥感图像目标检测。E-mail： xudanqing@nuaa.edu.cn
XU Danqing
* ,
- role：Corresponding author通信作者
- Affiliation：
  College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
- Email：nuaaimage@163.com
- Introduction：吴一全，研究方向为遥感图像处理与理解、目标检测与识别、视频处理与智能分析、视觉检测与图像测量等。E-mail： nuaaimage@163.com
WU Yiquan
*
Vol. 28, Issue 12, Pages: 3045-3073(2024)
DOI：10.11834/jrs.20243166
Accepted：

Scan QR Code

Scan QR Code

Quote
Translate The Full Text
DOI：
DOI：

AI Introduction
Full Text(HTML)
Figs( 15 ) Tabs( 21 )
References
Publication Info
Metrics

Alert me when the article has been cited

Submit

Related Articles

A deep learning-based early forest fire detection method integrating visible light and thermal infrared images from unmanned aerial vehicles

A high-resolution remote sensing cropland field parcel dataset for the middle Yangtze River plain region

Revegetation detection method for rare earth mining areas using YOLOv8n network with integrated global features

BHDSI： A remote sensing building height dataset for deep learning

Remote sensing inversion of particulate organic carbon in inland waters based on biochemical-optical mechanisms

Related Author

YANG Dianqing 福州大学经济与管理学院

WU Junjie 福州大学经济与管理学院

XIE Junyang 华中师范大学城市与环境科学学院;华中师范大学前沿交叉研究院

LIN Anqi 华中师范大学城市与环境科学学院;华中师范大学前沿交叉研究院

ZHANG Rui 华中师范大学城市与环境科学学院;华中师范大学前沿交叉研究院

LUO Yubo 华中师范大学城市与环境科学学院;华中师范大学前沿交叉研究院

WU Wenbin 中国农业科学院农业资源与农业区划研究所

YU Qiangyi 中国农业科学院农业资源与农业区划研究所

Related Institution

School of Economics and Management, Fuzhou University

College of Urban and Environmental Sciences, Central China Normal University

Academy of Frontier Interdisciplinary Research, Central China Normal University

Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences

Geospatial Information Engineering Team, Jiangxi Provincial Geological Bureau