• Laser & Optoelectronics Progress
  • Vol. 59, Issue 24, 2410003 (2022)
Hao Ding, Huiqin Wang*, and Ke Wang
Author Affiliations
  • College of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an 710055, Shaanxi, China
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    DOI: 10.3788/LOP202259.2410003 Cite this Article Set citation alerts
    Hao Ding, Huiqin Wang, Ke Wang. Improved YOLOv3 Flame Detection Algorithm Based on Dynamic Shape Feature Extraction and Enhancement[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410003 Copy Citation Text show less
    Network structure of flame detection algorithm
    Fig. 1. Network structure of flame detection algorithm
    Conv_ block structure comparison before and after improvement
    Fig. 2. Conv_ block structure comparison before and after improvement
    Comparison between 3×3 standard convolution and deformable convolution. (a) Standard convolution; (b)-(d) deformable convolution
    Fig. 3. Comparison between 3×3 standard convolution and deformable convolution. (a) Standard convolution; (b)-(d) deformable convolution
    Diagram of standard convolution fixed receptive field and deformable convolution adaptive receptive field
    Fig. 4. Diagram of standard convolution fixed receptive field and deformable convolution adaptive receptive field
    Variation of network iteration loss
    Fig. 5. Variation of network iteration loss
    Comparison of detection effects of different algorithms. (a) Proposed algorithm; (b) YOLOv4; (c) Cascade R-CNN
    Fig. 6. Comparison of detection effects of different algorithms. (a) Proposed algorithm; (b) YOLOv4; (c) Cascade R-CNN
    ModelYOLOv3 and its improvementAP /%Speed /(frame·s-1Model volume /MB
    ADarkNet5389.0670.41246
    BResNet50_vd-DCN(stage 5)90.3083.19181
    CResNet50_vd-DCN(stage 4)90.1081.52181
    DResNet50_vd-DCN(stage 4,stage 5)93.8177.38182
    ED+Drop Block94.0277.38182
    FE+IoU Aware(ours)94.1173.52184
    Table 1. Ablation experiment
    ModelAlgorithmAP /%Speed /(frame·s-1Model volume /MB
    1Faster R-CNN90.435.28301
    2Cascade R-CNN90.8712.96355
    3YOLOv389.0670.41246
    4YOLOv3_IoULoss89.1270.55247
    5YOLOv490.8460.41266
    6RetinaNet_R5090.1061.92229
    7Propose algorithm94.1173.52184
    Table 2. Comparison of different target detection algorithms
    Hao Ding, Huiqin Wang, Ke Wang. Improved YOLOv3 Flame Detection Algorithm Based on Dynamic Shape Feature Extraction and Enhancement[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2410003
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