Improved YOLO V3 Algorithm and Its Application in Small Target Detection

Moran Ju; Haibo Luo; Zhongbo Wang; Miao He; Zheng Chang; Bin Hui

doi:10.3788/AOS201939.0715004

Acta Optica Sinica, Volume. 39, Issue 7, 0715004(2019)

Improved YOLO V3 Algorithm and Its Application in Small Target Detection

Moran Ju^{1,2,3,4,5、*}, Haibo Luo^1,2,4,5, Zhongbo Wang^1,2,3,4,5, Miao He^1,2,3,4,5, Zheng Chang^1,2,4,5, and Bin Hui^1,2,4,5

Author Affiliations

¹ Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

² Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

³ University of Chinese Academy of Sciences, Beijing 100049, China

⁴ Key Laboratory of Opt-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China

⁵ The Key Laboratory of Image Understanding and Computer Vision, Shenyang, Liaoning 110016, China

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Figures & Tables(12)

Fig. 1. YOLO V3 network structure

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Fig. 2. Structural unit of Darknet53. (a) ResNet unit; (b) DBL unit

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Fig. 3. K-means clustering analysis result

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Fig. 4. Output structure of each network. (a) YOLO V3 network; (b) improved YOLO V3 network

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Fig. 5. Improved YOLO V3 network structure

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Fig. 6. Improved YOLO V3 loss curve and Avg IOU curve. (a) Loss function curve; (b) Avg IOU curve

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Fig. 7. AP curves of each network. (a) AP curve of YOLO V3; (b) AP curve of improved YOLO V3

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Fig. 8. Comparison of detection results obtained by improved YOLO V3 algorithm and original YOLO V3 algorithm for small object

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Fig. 9. Comparison of detection results obtained by improved YOLO V3 algorithm and original YOLO V3 algorithm for small object

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Table 1. Number of each target in VEDAI dataset
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Table 1. Number of each target in VEDAI dataset
Class name Boat Camping Car Others Pickup Tractors Truck Vans Airplane
Total number 170 390 1340 200 950 190 300 100 47

Table 2. Comparison of target recognition results with different algorithms
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Table 2. Comparison of target recognition results with different algorithms
Detection algorithm X_TP X_FP X_FN P /% R /%
YOLO V3 373 69 57 84.3 86.7
Improved YOLO V3 392 56 37 87.5 91.2

Table 3. Comparison of target detection results with different algorithms
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Table 3. Comparison of target detection results with different algorithms
Detection algorithm AP /% mAP /%
Boat Camping Car Others Pickup Tractors Truck Vans Plane
YOLO V3 21 61 78 22 70 43 55 52 100 55.81
Improved YOLO V3 42 61 81 34 76 66 31 70 100 62.36

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Moran Ju, Haibo Luo, Zhongbo Wang, Miao He, Zheng Chang, Bin Hui. Improved YOLO V3 Algorithm and Its Application in Small Target Detection[J]. Acta Optica Sinica, 2019, 39(7): 0715004

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