Real-Time Target Detection Method Applied to Embedded Graphic Processing Unit

Fig. 3. Comparison of partial detection results in third group of experiments. (a)-(e) Results by YOLO-V3; (f)-(j) results by proposed network structure

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Fig. 4. Detection results on embedded platform. (a) YOLO-V3; (b) YOLO-tiny; (c) proposed network structure; (d) MobileNet-V1-SSD; (e) MobileNet-V2-SSD

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Table 1. Results of first group of experiments
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Table 1. Results of first group of experiments
Model P_mAP /% R /%
YOLO-V3 86.20 85.49
YOLO-tiny 65.89 75.56
Proposed method 64.22 78.22

Table 2. Results of second group of experiments
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Table 2. Results of second group of experiments
Model P_mAP /% R /%
YOLO-V3 72.48 78.96
YOLO-tiny 56.32 67.77
Proposed method 52.87 69.13

Table 3. Results of third group of experiments
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Table 3. Results of third group of experiments
Model P_mAP /% R /%
YOLO-V3 89.29 81.76
YOLO-tiny 72.40 69.13
Proposed method 71.35 73.90

Table 4. Speed comparison of target detection
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Table 4. Speed comparison of target detection
Model Average speed on TX1 /(frame·s^-1)
MobileNet-V1-SSD 14
MobileNet-V2-SSD 13
YOLO-V3 2
YOLO-tiny 17
Proposed method 23

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Xiaoqing Wang, Xiangjun Wang. Real-Time Target Detection Method Applied to Embedded Graphic Processing Unit[J]. Acta Optica Sinica, 2019, 39(3): 0315005

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