• Journal of Applied Optics
  • Vol. 44, Issue 5, 1054 (2023)
Shuli LOU1, Yan WANG1,*, Jianqin GUO2, and Weifeng GONG3
Author Affiliations
  • 1School of Physics and Electronic Information, Yantai University, Yantai 264005, China
  • 2Department of Electronics and Communication Engineering, Shandong College of Electronic Technology, Jinan 250200, China
  • 3State Key Laboratory of High-end Server and Storage Technology, Jinan 250101, China
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    DOI: 10.5768/JAO202344.0502006 Cite this Article
    Shuli LOU, Yan WANG, Jianqin GUO, Weifeng GONG. Infrared ship target detection algorithm based on improved YOLOX-S[J]. Journal of Applied Optics, 2023, 44(5): 1054 Copy Citation Text show less
    YOLOX-S network structure model
    Fig. 1. YOLOX-S network structure model
    Improved YOLOX-S network structure model
    Fig. 2. Improved YOLOX-S network structure model
    Traditional convolution structure
    Fig. 3. Traditional convolution structure
    Depthwise separable convolution structure
    Fig. 4. Depthwise separable convolution structure
    ECANet channel attention mechanism
    Fig. 5. ECANet channel attention mechanism
    Comparison of detection effect
    Fig. 6. Comparison of detection effect
    ModelBackbonePrecision%AP%FPSParams
    Faster R-CNNResNet-500.980.974108.6 M
    SSDVGG0.950.924799.76 M
    YOLOv4MobileNetv20.940.925241.2 M
    YOLOv5-sCSPDarknet0.940.945427.76 M
    YOLOX-SCSPDarknet0.960.955034.21 M
    Improved YOLOX-SCSPDarknet0.980.985625.79 M
    Table 1. Comparison of different algorithms
    DSCECANetLoss_CIoUAP%FPSParams
    ---0.955034.21 M
    √---√---√0.940.970.9658495025.79 M34.21 M34.21 M
    -0.975625.79 M
    0.985625.79 M
    Table 2. Comparison of ablation experiment results
    Shuli LOU, Yan WANG, Jianqin GUO, Weifeng GONG. Infrared ship target detection algorithm based on improved YOLOX-S[J]. Journal of Applied Optics, 2023, 44(5): 1054
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