A Graph Convolutional Network Framework for Area Attention and Tracking Compensation of In-Orbit Satellite
In order to solve the problems of low tracking accuracy of in-orbit satellites by ground stations and slow processing speed of satellite target tracking images, this paper proposes an orbital satellite regional tracking and prediction model based on graph convolutional networks (GCNs). By performing...
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Main Authors: | Shuai Wang, Ruoke Wu, Yizhi Jiang, Xiaoqiang Di, Yining Mu, Guanyu Wen, Makram Ibrahim, Jinqing Li |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-06-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/12/6742 |
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