Simulation Research on Appearance Detection of Ampoules Based on Lightweight Network and Model Compression

Authors

Zhihao Zhu, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;Follow
Yan Wang, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;Follow
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Jiangnan University, Wuxi 214122, China;

Abstract

Abstract: Aiming at the large scale and redundant parameters of target detection network model, which result in the difficult to deploy the ampoule bottle appearance defect detection model to edge devices, an LC-Faster R-CNN defect detection algorithm based on lightweight network and model compression is proposed. MobileNet-V2 is used as the backbone, and the redundant channels in the convolutional network are trimmed by model pruning strategy. The floating-point parameters are quantized into integers through saturation truncation mapping. Knowledge distillation is used to restore the accuracy of the compressed network. Tested on the self-built ampoule appearance defect dataset, the model volume is reduced by 69.6% and the average accuracy is 89.3%. The simulation results show that the compressed target detection model can meet the requirements of the appearance detection of ampoules in practical applications.

Recommended Citation

Zhu, Zhihao; Wang, Yan; and Ji, Zhicheng (2022) "Simulation Research on Appearance Detection of Ampoules Based on Lightweight Network and Model Compression," Journal of System Simulation: Vol. 34: Iss. 12, Article 7.
DOI: 10.16182/j.issn1004731x.joss.22-FZ0925
Available at: https://dc-china-simulation.researchcommons.org/journal/vol34/iss12/7

First Page

2575

Revised Date

2022-09-09

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.22-FZ0925

Last Page

2583

CLC

TP391.4

Recommended Citation

Zhihao Zhu, Yan Wang, Zhicheng Ji. Simulation Research on Appearance Detection of Ampoules Based on Lightweight Network and Model Compression[J]. Journal of System Simulation, 2022, 34(12): 2575-2583.

Corresponding Author

Yan Wang,wangyan@jiangnan.edu.cn

DOI

10.16182/j.issn1004731x.joss.22-FZ0925