Research on the Application of Object Detection in the Installation of Spacer Bars
| Autor: | Yunxiang Zhu, Fa Wang, Qianxi Chen, Ling Li |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Physics: Conference Series. 2303:012075 |
| ISSN: | 1742-6596 1742-6588 |
| DOI: | 10.1088/1742-6596/2303/1/012075 |
| Popis: | The correct installation of spacer bars is an important part of ensuring people’s daily life. This paper studies and implements a spacer bar installation confirmation system based on a deep learning object detection algorithm, which makes up for the deficiencies in the installation. Among the object detection algorithms, Faster-RCNN has higher detection accuracy, is more accurate than one-stage and can detect multi-scale and small objects. Through historical use, it is found that Faster-RCNN is excellent in detecting multi-class image sets tasks. For personal data sets, only fine-tuning is needed to achieve better results, and it also has a fast detection rate. Therefore, this paper is based on the Faster-RCNN algorithm to realize the detection and confirmation of the plug and rubber during the installation of the spacer bar. |
| Databáze: | OpenAIRE |
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