Geospatial Transformer Is What You Need for Aircraft Detection in SAR Imagery-Reference-Cited by-同舟云学术

Geospatial Transformer Is What You Need for Aircraft Detection in SAR Imagery

Published:2022 Issue: Volume:60 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Chen Lifu¹^ORCID,Luo Ru¹^ORCID,Xing Jin²^ORCID,Li Zhenhong³^ORCID,Yuan Zhihui¹^ORCID,Cai Xingmin¹^ORCID

Affiliation:

1. School of Electrical and Information Engineering and the Laboratory of Radar Remote Sensing Applications, Changsha University of Science and Technology, Changsha, China

2. School of Engineering, Newcastle University, Newcastle upon Tyne, U.K

3. College of Geological Engineering and Geomatics, Chang’an University, Xi’an, China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, Chang'an University

Scientific Research Fund of the Hunan Provincial Education Department

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/9633014/09741706.pdf?arnumber=9741706

Reference50 articles.

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3. CSPNet: A New Backbone that can Enhance Learning Capability of CNN

4. Sampling based image splitting in large scale distributed computing of earth observation data;xing;Proc IEEE Geosci Remote Sens Symp,2014

5. A Multi-Scale Deep Neural Network for Water Detection from SAR Images in the Mountainous Areas

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