Researching | Prohibited Item Identification Algorithm Based onLightweight Segmentation Network

Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0210022(2021)

Prohibited Item Identification Algorithm Based onLightweight Segmentation Network

Shaoqing Yao¹ and Zhigang Su^1,2、*

Author Affiliations

¹Tianjin Key Laboratory for Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China

²Sino-European Institute of Aviation Engineering, Civil Aviation University of China, Tianjin 300300, China

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References (23)

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Figures & Tables(9)

Fig. 1. Prohibited item identification model

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Fig. 2. Results of data augmentation

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Fig. 3. Dilated convolution module. (a) Without feature multiplexing operation; (b) with 3-layer convolution; (c) with 2-layer convolution

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Fig. 4. Asymmetric convolution module. (a) Downsampling; (b) upsampling

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Fig. 5. Example of images in dataset

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Fig. 6. Segmentation results of contrast experiment

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Fig. 7. Segmentation results of ablation experiment

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Table 1. Results of contrast experiment
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Table 1. Results of contrast experiment
Algorithm mIoU /10^-2 Time /ms FPS
FCN8s 62.15 120 8.3
PSPNet 70.56 152 6.5
Deeplabv3 71.15 162 6.1
An's model 74.51 276 3.6
ENet 51.21 7 128.7
Proposed algorithm 73.18 36 27.1

Table 2. Results of ablation experiment
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Table 2. Results of ablation experiment
Algorithm mIoU /10^-2 Time /ms FPS
Group 1 63.28 61 16.3
Group 2 69.75 84 11.8
Group 3 68.30 58 17
Group 4 67.37 33 29.5
Group 5 67.84 40 25
Proposed algorithm 73.18 36 27.1

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Shaoqing Yao, Zhigang Su. Prohibited Item Identification Algorithm Based onLightweight Segmentation Network[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0210022

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Paper Information

Category: Image Processing

Received: Jun. 24, 2020

Accepted: Jul. 20, 2020

Published Online: Jan. 8, 2021

The Author Email: Zhigang Su (ssrsu@vip.sina.com)

DOI:10.3788/LOP202158.0210022

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology