• Laser & Optoelectronics Progress
  • Vol. 59, Issue 12, 1210011 (2022)
Kewen Li1, Baohua Zhang1、3、*, Xiaoqi Lv2、3, Yu Gu1、3, Yueming Wang1、3, Xin Liu1、3, Yan Ren1, Jianjun Li1、3, and Ming Zhang1、3
Author Affiliations
  • 1School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, Inner Mongolia , China
  • 2School of Information Engineering, Mongolia Industrial University, Huhehaote010051, Inner Mongolia , China
  • 3Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing, Baotou 014010, Inner Mongolia , China
  • show less
    DOI: 10.3788/LOP202259.1210011 Cite this Article Set citation alerts
    Kewen Li, Baohua Zhang, Xiaoqi Lv, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Remote Sensing Aircraft Detection Based on Smooth Label and Multipath Aggregation Network[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1210011 Copy Citation Text show less
    References

    [1] Dai Y, Yi B S, Xiao J S et al. Object detection of remote sensing image based on improved rotation region proposal network[J]. Acta Optica Sinica, 40, 0111020(2020).

    [2] Dong Y F, Zhang C T, Wang P et al. Airplane detection of optical remote sensing images based on deep learning[J]. Laser & Optoelectronics Progress, 57, 041007(2020).

    [3] Wang Y N, Wang X L. Remote sensing image target detection model based on attention and feature fusion[J]. Laser & Optoelectronics Progress, 58, 0228003(2021).

    [4] Xu J F, Zhang B M, Yu D H et al. Aircraft target change detection for high-resolution remote sensing images using multi-feature fusion[J]. Journal of Remote Sensing, 24, 37-52(2020).

    [5] Huang W, Li G Y, Chen Q Q et al. CF2PN: a cross-scale feature fusion pyramid network based remote sensing target detection[J]. Remote Sensing, 13, 847(2021).

    [6] Qiu H Q, Li H L, Wu Q B et al. A2RMNet: adaptively aspect ratio multi-scale network for object detection in remote sensing images[J]. Remote Sensing, 11, 1594(2019).

    [7] Chen C Y, Gong W G, Chen Y L et al. Object detection in remote sensing images based on a scene-contextual feature pyramid network[J]. Remote Sensing, 11, 339(2019).

    [8] Wang C Y, Liao H Y M, Wu Y H et al. CSPNet: A new backbone that can enhance learning capability of CNN[C], 390-391(2020).

    [9] Bochkovskiy A, Wang C Y, Liao H Y M. YOLOv4: optimal speed and accuracy of object detection[EB/OL]. https://arxiv.org/abs/2004.10934

    [10] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018, 11211, 3-19(2018).

    [11] Liu S, Qi L, Qin H F et al. Path aggregation network for instance segmentation[C], 8759-8768(2018).

    [12] Yang X, Yan J C. Arbitrary-oriented object detection with circular smooth label[M]. Vedaldi A, Bischof H, Brox T, et al. Computer vision-ECCV 2020, 12353, 677-694(2020).

    [13] Müller R, Kornblith S, Hinton G E. When does label smoothing help?[EB/OL]. https://arxiv.org/abs/1906.02629

    [14] Long Y, Gong Y P, Xiao Z F et al. Accurate object localization in remote sensing images based on convolutional neural networks[J]. IEEE Transactions on Geoscience and Remote Sensing, 55, 2486-2498(2017).

    [15] Zhang Y L, Yuan Y, Feng Y C et al. Hierarchical and robust convolutional neural network for very high-resolution remote sensing object detection[J]. IEEE Transactions on Geoscience and Remote Sensing, 57, 5535-5548(2019).

    Kewen Li, Baohua Zhang, Xiaoqi Lv, Yu Gu, Yueming Wang, Xin Liu, Yan Ren, Jianjun Li, Ming Zhang. Remote Sensing Aircraft Detection Based on Smooth Label and Multipath Aggregation Network[J]. Laser & Optoelectronics Progress, 2022, 59(12): 1210011
    Download Citation