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Journals >
Laser & Optoelectronics Progress >
Volume 57 >
Issue 10 >
Page 101507 > Article
Laser & Optoelectronics Progress
Vol. 57, Issue 10, 101507 (2020)
Improved Real-Time Vehicle Detection Method Based on YOLOV3
Hanbing Li
*
, Chunyang Xu, and Chaochao Hu
Author Affiliations
School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang, Jiangsu 212013, China
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DOI:
10.3788/LOP57.101507
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Hanbing Li, Chunyang Xu, Chaochao Hu. Improved Real-Time Vehicle Detection Method Based on YOLOV3[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101507
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Fig. 1.
Inverted residual network. (a) Stride is 1; (b) stride is 2
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Fig. 2.
Feature maps of different sizes in the last three layers of network. (a) 52×52; (b) 26×26; (c) 13×13
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Fig. 3.
Improved network structure
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Fig. 4.
P-R curves for different models
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Fig. 5.
Model detection results in different scenarios. (a) Original images; (b) detection results of YOLOV3; (c) detection results of improved model
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Model
Layer
Parameter
Size /MB
SSD
88
27188676
103
YOLOV2
75
50983561
194
YOLOV3
256
61587112
235
Proposed
223
22314120
85.6
Table 1.
Comparison of network layers and sizes of different models
Improvement strategy
Inverted residuals
GN
SoftNMS
Focal-loss
Change of mAP /%
-3.17
1.15
1.39
1.78
Table 2.
Influence of different improvement strategies on mAP
Model
mAP /%
Time /ms
SSD
89.88
48.8
YOLOV2
89.60
30.2
YOLOV3
91.91
42.3
Proposed
93.06
28.5
Table 3.
Comparison of test results of different models
Abstract
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Hanbing Li, Chunyang Xu, Chaochao Hu. Improved Real-Time Vehicle Detection Method Based on YOLOV3[J]. Laser & Optoelectronics Progress, 2020, 57(10): 101507
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Paper Information
Category: Machine Vision
Received: Aug. 5, 2019
Accepted: Oct. 22, 2019
Published Online: May. 8, 2020
The Author Email: Li Hanbing (1340733996@qq.com)
DOI:
10.3788/LOP57.101507
Recommended Topics
laser devices and laser physics
Lasers and Laser Optics
Laser physics
laser manufacturing
Instrumentation, Measurement and Metrology
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