• Electronics Optics & Control
  • Vol. 30, Issue 7, 63 (2023)
HUANG Yuling1, TAO Xinchen1, ZHU Tao1, SI Junwen1, LYU Changdong1, WU Di1, and SHEN Zhanfeng1、2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3969/j.issn.1671-637x.2023.07.011 Cite this Article
    HUANG Yuling, TAO Xinchen, ZHU Tao, SI Junwen, LYU Changdong, WU Di, SHEN Zhanfeng. A Remote Sensing Image Detection Method Based on Residuals Adversarial Object Detection Algorithm[J]. Electronics Optics & Control, 2023, 30(7): 63 Copy Citation Text show less

    Abstract

    Aiming at the problems of small object scale and low resolution in remote sensing image object detection,a remote sensing image detection method based on residual adversarial object detection algorithm is proposed in this paper.The feature information of the image is reconstructed through residual adversarialism,so as to realize the improvement of image resolution.Based on image feature information which is extracted by Backbone network,the features are fused by Neck structure.Finally,the CIoU_Loss function is designed to increase the regression accuracy,and improve model performance.Experimental results show that,compared with other algorithms,the mean precision,mean recall,mean F1-score and mean mAP value of this algorithm are improved by 8.15%,6.9%,7.15% and 6.75% respectively.The algorithm has high accuracy in object detection in low-resolution remote sensing images,and has good effect on small object detection in remote sensing images.
    HUANG Yuling, TAO Xinchen, ZHU Tao, SI Junwen, LYU Changdong, WU Di, SHEN Zhanfeng. A Remote Sensing Image Detection Method Based on Residuals Adversarial Object Detection Algorithm[J]. Electronics Optics & Control, 2023, 30(7): 63
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