• Journal of Applied Optics
  • Vol. 45, Issue 4, 723 (2024)
Haiyong CHEN1, Dengbin LIU1, and Xingwei YAN2、3、*
Author Affiliations
  • 1School of Artificial Intelligence and Data Science, Hebei University of Technology, Tianjin 300401, China
  • 2College of Electronic Science, National University of Defense Technology, Changsha 410073, China
  • 3Tianjin Institute of Advanced Technology, Tianjin 300459, China
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    DOI: 10.5768/JAO202445.0402001 Cite this Article
    Haiyong CHEN, Dengbin LIU, Xingwei YAN. Infrared image UAV target detection algorithm based on IDOU-YOLO[J]. Journal of Applied Optics, 2024, 45(4): 723 Copy Citation Text show less
    IDOU-YOLO algorithm model
    Fig. 1. IDOU-YOLO algorithm model
    Structure diagram of MMFPN and common neck network
    Fig. 2. Structure diagram of MMFPN and common neck network
    Schematic diagram of MMFPN path
    Fig. 3. Schematic diagram of MMFPN path
    Schematic diagram of SIOU loss parameters
    Fig. 4. Schematic diagram of SIOU loss parameters
    Images of detection results for algorithm
    Fig. 5. Images of detection results for algorithm
    ModelP/%R/%PmAP@ 0.5/%PmAP@ 0.5:0.95/%F1/%FPS
    YOLOv798.994.297.067.696.593.5
    IDOU-YOLO99.296.398.470.297.779.4
    Table 1. Overall properties of IDOU-YOLO and YOLOv7 on anti-UAV dataset
    NeckP/%R/%PmAP@ 0.5/%PmAP@ 0.5:0.95/%F1/%FPS
    FPN97.689.295.666.293.2123.5
    PANet98.696.098.069.497.395.2
    BiFPN98.796.298.470.197.495.2
    MMFPN99.296.398.470.297.779.4
    Table 2. Experimental results of performance of neck network comparison
    LossP/%R/%PmAP@0.5/%PmAP@0.5:0.95/%F1/%
    DIoU99.196.098.069.797.5
    GIoU98.796.397.969.797.5
    CIoU99.695.498.469.997.5
    SIoU99.296.398.470.297.7
    Table 3. Experimental results of bounding box loss function comparison
    ModelP/%R/%PmAP@0.5/%F1/%FPS
    Faster-RCNN34.766.052.345.519.2
    SSD98.860.086.174.774.1
    Retinanet99.760.965.875.639.5
    Centernet98.685.991.191.866.2
    FCOS98.781.991.989.541.6
    YOLOX98.889.893.194.137.9
    YOLOv599.195.798.297.463.3
    IDOU-YOLO99.296.398.497.779.4
    Table 4. Comparative experimental results of IDOU-YOLO and mainstream target detection algorithms
    Haiyong CHEN, Dengbin LIU, Xingwei YAN. Infrared image UAV target detection algorithm based on IDOU-YOLO[J]. Journal of Applied Optics, 2024, 45(4): 723
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