Computer Science ›› 2022, Vol. 49 ›› Issue (6A): 378-383.doi: 10.11896/jsjkx.210300121

• Image Processing & Multimedia Technology • Previous Articles     Next Articles

Remote Sensing Aircraft Target Detection Based on Improved Faster R-CNN

ZHU Wen-tao1, LAN Xian-chao1, LUO Huan-lin1, YUE Bing2, WANG Yang1   

  1. 1 Shanghai Academy of Spaceflight Technology,Shanghai 201109,China
    2 Beijing Aeronautical Technology Research Center,Beijing 100020,China
  • Online:2022-06-10 Published:2022-06-08
  • About author:ZHU Wen-tao,born in 1995,master,engineer.His main research interests include on-board intelligent processing and object detection.

Abstract: Optical remote sensing image airplane target detection technology has been widely used in the fields of air traffic and military reconnaissance.Aiming at the problem of low detection accuracy and high false alarm rate when detecting multiple aircraft of different sizes,this paper proposes an improved ROI pooling method based on bilinear interpolation for aircraft target detection,which solves the problem of mis-alignment.Experimental results show that the improved method achieves a detection performance of 95.35% AP(IOU≤0.5).In the task of multi-size airplane detection,the target positioning accuracy and average accuracy are improved.

Key words: Airplane target detection, Deep learning, Faster R-CNN, Remote sensing image, ROI pooling

CLC Number: 

  • TP753
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