Remote sensing image target detection based on a multi-scale deep feature fusion network

Remote Sensing Intelligent Interpretation | Views:5035Downloads:3929CSCD:12

Export
Share
Collection
Album

Remote sensing image target detection based on a multi-scale deep feature fusion network
- role：First author第一作者
- Affiliation：
  Hohai University, College of Internet of Things Engineering, Changzhou 213022, China
- Email：fanxn@hhuc.edu.cn
- Introduction：范新南，研究方向为图像处理和机器视觉。E-mail： fanxn@hhuc.edu.cn
FAN Xinnan
* ,
- Affiliation：
  Hohai University, College of Internet of Things Engineering, Changzhou 213022, China
YAN Wei
* ,
- role：Corresponding author通信作者
- Affiliation：
  Hohai University, College of Internet of Things Engineering, Changzhou 213022, China
- Email：shipf@hhu.edu.cn
- Introduction：史朋飞，研究方向为多源信息融合和图像处理。E-mail： shipf@hhu.edu.cn
SHI Pengfei
* ,
- Affiliation：
  Hohai University, College of Internet of Things Engineering, Changzhou 213022, China
ZHANG Xuewu
*
Vol. 26, Issue 11, Pages: 2292-2303(2022)
DOI：10.11834/jrs.20210170
Accepted：

Scan QR Code

Scan QR Code

Quote
Translate The Full Text
DOI：
DOI：

Full Text(HTML)
Figs( 17 ) Tabs( 4 )
References
Publication Info
Metrics

摘要

Abstract

关键词

Keywords

references

Alert me when the article has been cited

Submit

Related Articles

Few-shot object detection in optical remote sensing images

Object detection in remote sensing images using densely connected recursive feature pyramids

Application of an improved CenterNet in remote sensing images object detection

Feature attention pyramid-based remote sensing image object detection method

Top ten frontier scientific issues in the field of remote sensing science and technology

Related Author

范新南河海大学物联网工程学院

严炜河海大学物联网工程学院

史朋飞河海大学物联网工程学院

张学武河海大学物联网工程学院

ZHOU Lian 武汉大学计算机学院

HE Chu 武汉大学电子信息学院

WANG Dingwen 武汉大学计算机学院

GUO Ziqi 武汉大学计算机学院

Related Institution

河海大学物联网工程学院

School of Computer Science, Wuhan University

School of Electronic Information, Wuhan University

College of Combat Support, Rocket Force University of Engineering

State Key Laboratory of Complex Electromagnetic Environment Effects on Electronics and Information System (CEMEE)