• Acta Optica Sinica
  • Vol. 41, Issue 10, 1028001 (2021)
Yuanjun Nong and Junjie Wang*
Author Affiliations
  • School of Engineering, Ocean University of China, Qingdao, Shandong 266100, China
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    DOI: 10.3788/AOS202141.1028001 Cite this Article Set citation alerts
    Yuanjun Nong, Junjie Wang. Real-Time Object Detection in Remote Sensing Images Based on Embedded System[J]. Acta Optica Sinica, 2021, 41(10): 1028001 Copy Citation Text show less
    Network structure of YOLOv3-tiny
    Fig. 1. Network structure of YOLOv3-tiny
    Detection flow of YOLOv3-tiny
    Fig. 2. Detection flow of YOLOv3-tiny
    52×52 scale shallow features and 26×26 scale deep features
    Fig. 3. 52×52 scale shallow features and 26×26 scale deep features
    Multi-scale prediction structure. (a) Multi-scale prediction before modified; (b) multi-scale prediction after modified
    Fig. 4. Multi-scale prediction structure. (a) Multi-scale prediction before modified; (b) multi-scale prediction after modified
    Spatial attention module. (a) Original spatial attention module; (b) modified spatial attention module
    Fig. 5. Spatial attention module. (a) Original spatial attention module; (b) modified spatial attention module
    Network structure of YOLO-RS
    Fig. 6. Network structure of YOLO-RS
    Loss curve during training process
    Fig. 7. Loss curve during training process
    Test results of YOLO-RS
    Fig. 8. Test results of YOLO-RS
    Experiments on the embedded platform Jetson Xavier NX
    Fig. 9. Experiments on the embedded platform Jetson Xavier NX
    Comparison of detection accuracy and speed of different models
    Fig. 10. Comparison of detection accuracy and speed of different models
    MethodInput sizemAP /%Recall /%F1 /%BFLOPSVolume /MB
    YOLOv3608×60880.078181139.64246.5
    YOLOv3-tiny608×60873.09677211.6734.8
    YOLO-RS608×60876.7075787.0410.0
    YOLOv3512×51279.61768099.02246.5
    YOLOv3-tiny512×51271.6063708.2734.8
    YOLO-RS512×51275.5673774.9910.0
    YOLOv3416×41677.04707765.37246.5
    YOLOv3-tiny416×41665.1554645.4634.8
    YOLO-RS416×41672.8665723.3010.0
    Table 1. Detection performance of different methods on remote sensing test set
    MethodSpeed /(frame·s-1)
    416×416512×512608×608
    YOLOv38.16.34.6
    YOLOv3-tiny54.640.831.5
    YOLO-RS56.743.532.5
    Table 2. Detection speed of different methods on Jetson Xavier NX
    Yuanjun Nong, Junjie Wang. Real-Time Object Detection in Remote Sensing Images Based on Embedded System[J]. Acta Optica Sinica, 2021, 41(10): 1028001
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