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Journal of Projectiles, Rockets, Missiles and Guidance >

2023 , Vol. 43 >Issue 1: 24 - 31

DOI: https://doi.org/10.15892/j.cnki.djzdxb.2023.01.004

CenterNet-based Target Detection Method for Remote Sensing Images

  • HUANG Jiaqi 1, 2 ,
  • FAN Junfang 1, 2 ,
  • LI Beibei 3
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  • 1 Beijing Key Laboratory of High Dynamic Navigation Technology, Beijing Information Science and Technology University, Beijing 100192, China
  • 2 School of Automation, Beijing Information Science and Technology University, Beijing 100192, China
  • 3 No.32381 Unit, Beijing 100072, China

Received date: 2022-09-11

  Online published: 2025-02-01

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Abstract

Fast and accurate identification of small and dense targets in low quality remote sensing images has become a focus of research community. A CenterNet-based target detection method that incorporates the attention mechanism is proposed. It utilizes ResNet-50 for basic feature extraction. An improved channel attention module (ECA-NET) is introduced at the backbone output to weaken the expression of non-concerned points, while enhancing the information channel of concerned points. The proposed method adjusts the learning strategy in different stages to accelerate the convergence speed of the model. Experiments are conducted using the remote sensing dataset. The improved CenterNet algorithm increases the accuracy by 13% as compared with the original method, and the detection speed reaches 52.61 frames per second. The experimental results show that CenterNet-based target detection method maximizes the remote sensing target representation capability of CenterNet under the condition of maintaining computational efficiency. It effectively balances the accuracy and computation speed of remote sensing target detection and is of great significance in practical applications.

Key words： deep learning; target detection; anchor-free; CenterNet; attention mechanism

Cite this article

HUANG Jiaqi , FAN Junfang , LI Beibei . CenterNet-based Target Detection Method for Remote Sensing Images[J]. Journal of Projectiles, Rockets, Missiles and Guidance, 2023 , 43(1) : 24 -31 . DOI: 10.15892/j.cnki.djzdxb.2023.01.004

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