Laser & Optoelectronics Progress, Volume. 62, Issue 8, 0837003(2025)
Cotter Pin Detection of Transmission Line Based on YOLOv8-DEA
Figures & Tables(11)
Fig. 3. Attention structure. (a) EMLLA structure; (b) MLLA structure; (c) linear attention structure; (d) EMLP structure
Fig. 5. Some images from the dataset. (a) Pin_bolt; (b) pin_defect; (c) pin_loose
Fig. 6. Comparison of experimental results. (a) Original pictures; (b) YOLOv9 test results; (c) YOLOv8 test results; (d) YOLOv8-DEA test results
Fig. 7. Comparison of experimental results. (a) Original pictures; (b) YOLOv9 test results; (c) YOLOv8 test results; (d) YOLOv8-DEA test results
Table 1. Comparison of ablation experiment results
View tableTable 1. Comparison of ablation experiment results
Model mAP@0.5 /% R@0.5 /% P /% FPS /（frame/s） Parameter /MByte Size /MByte GFlops /MByte YOLOv8 89.51 84.29 95.15 97.67 25.86 98.92 79.07 YOLOv8-D 90.61 86.08 95.94 86.72 30.59 116.69 94.24 YOLOv8-E 90.60 86.83 95.81 84.42 31.53 120.28 83.60 YOLOv8-A 90.75 85.69 96.22 85.57 28.31 108.01 82.90 YOLOv8-DE 90.91 86.50 95.93 75.20 36.26 138.33 98.77 YOLOv8-DA 91.01 86.60 95.94 75.49 33.04 126.05 98.07 YOLOv8-EA 91.13 87.21 96.34 76.27 33.99 129.65 87.43 YOLOv8-DEA 91.84 87.96 95.58 67.84 38.72 147.70 102.60
Table 2. Performance comparison of different algorithms
View tableTable 2. Performance comparison of different algorithms
Model Backbone mAP@0.5 /% R@0.5 /% P /% FPS /（frame/s） Parameter /MByte Size /MByte GFlops /GByte SSD VGG16 87.72 77.95 94.14 55.88 23.88 91.09 274.05 FCOS ResNet 86.32 76.12 94.36 61.23 32.12 122.53 161.21 YOLOv5m_6.0 CSPDarkNet 53 89.14 85.23 93.52 99.69 20.88 79.65 48.25 YOLOX CSPDarkNet 53 91.36 87.86 94.59 84.65 25.28 96.44 73.73 YOLOv7 EfficientNet 90.35 83.06 94.59 45.17 37.21 142.69 105.14 YOLOv9 RepNCSPELAN4 91.42 85.94 93.86 70.23 25.34 97.32 103.28 RT-DETR ResNet-50 91.13 84.87 94.83 41.56 41.96 160.28 136.56 DAMO-YOLO MAE-NAS 90.25 82.81 93.67 86.42 28.23 107.57 63.89 YOLOv6 v3.0 EfficientRep 91.38 86.72 94.98 77.03 34.92 134.46 87.83 YOLOv8 CSPDarkNet53 89.51 84.29 95.15 97.67 25.86 98.92 79.07 Proposed CSPDarkNet53 91.84 87.96 95.58 67.84 38.72 147.70 102.60
Table 3. Comparison of VisDrone2019 experiment
View tableTable 3. Comparison of VisDrone2019 experiment
Model Backbone mAP@0.5 /% R@0.5 /% P /% FPS /（frame/s） Parameter /MByte Size /MByte GFlops /GByte Reference［ 25 ］CSPDarkNet 53 35.5 37.4 53.0 ‒ ‒ ‒ 22.60 Reference［ 26 ］‒ 35.3 43.2 35.5 ‒ ‒ ‒ ‒ Reference［ 27 ］CSPDarkNet 53 35.1 ‒ ‒ ‒ 31.5 ‒ 122.70 Reference［ 28 ］CSPDarkNet 53 38.9 ‒ ‒ ‒ 33.9 ‒ ‒ DTSSNet［ 29 ］MobileNetv2 24.2 ‒ ‒ 75.5 10.1 ‒ 50.30 YOLOv8 CSPDarkNet 53 41.3 42.5 52.1 94.8 25.9 98.9 79.07 Proposed CSPDarkNet 53 42.1 44.6 53.2 67.7 38.7 147.7 102.60
Table 4. Comparison of the detection accuracy between the proposed algorithm and other algorithms
View tableTable 4. Comparison of the detection accuracy between the proposed algorithm and other algorithms
Model Category Map Pedestrian Person Bicycle Car Van Truck Tricycle Awning Bus Motor Ref.［ 25 ］35.3 30.4 31.8 11.0 76.7 38.6 28.3 21.6 10.6 49.7 40.4 Ref.［ 26 ］35.3 42.3 32.8 8.8 78.2 39.0 30.9 22.2 11.7 47.7 39.1 Ref.［ 30 ］34.8 29.8 17.0 10.6 73.6 40.5 42.3 20.4 21.6 59.5 32.4 Ref.［ 27 ］35.1 36.3 23.6 12.4 76.8 40.0 26.8 18.5 18.4 56.3 31.8 Ref.［ 31 ］41.5 36.8 21.8 21.4 79.8 50.6 48.2 26.7 25.2 61.9 43.2 YOLOv8 41.3 45.5 34.7 16.2 80.8 45.2 38.8 29.5 16.2 59.6 46.9 Propsoed 42.1 41.3 35.2 13.8 80.1 42.9 41.8 30.7 25.6 62.4 47.2
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Kerui Wang, Chuncheng Zhou, Yi Ma, Lincong Peng, Hao Zhou, Pengfei Yu. Cotter Pin Detection of Transmission Line Based on YOLOv8-DEA[J]. Laser & Optoelectronics Progress, 2025, 62(8): 0837003
Paper Information
Category: Digital Image Processing
Received: Jul. 15, 2024
Accepted: Oct. 8, 2024
Published Online: Apr. 3, 2025
The Author Email: Pengfei Yu (pfyu@ynu.edu.cn)
CSTR:32186.14.LOP241686
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