Object detection and recognition system based on computer vision analysis
文献类型:期刊论文
作者 | Liu,Haitao1; Li,Yuge2; Liu,Dongchang1![]() |
刊名 | Journal of Physics: Conference Series
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出版日期 | 2021-07-01 |
卷号 | 1976期号:1 |
关键词 | post-epidemic artificial intelligence computer vision deep learning |
ISSN号 | 1742-6588 |
DOI | 10.1088/1742-6596/1976/1/012024 |
英文摘要 | Abstract Artificial intelligence based on deep learning enables the machine to have the ability of understanding and cognition, but the application of artificial intelligence technology in supermarket shopping scene is limited. In the post-epidemic era, the contactless self-checkout of unmanned supermarket is more in line with the development needs of modern society. We build Pytorch environment, first to collect pictures of a large number of commodities and labeling information, and training model is obtained by YOLO neural network algorithm, finally through a call to model to realize the recognition of goods. Neural network algorithm is used to improve the recognition rate of goods step by step and achieve the detection and recognition of objects. We have tested our model on the real supermarket commodity data set and the public data set ImageNet, and the results show that our model can achieve a certain practical effect. |
语种 | 英语 |
WOS记录号 | IOP:1742-6588-1976-1-012024 |
出版者 | IOP Publishing |
源URL | [http://ir.ia.ac.cn/handle/173211/45790] ![]() |
专题 | 综合信息系统研究中心_脑机融合与认知评估 |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences, Beijing, China 2.Renmin University of China, Beijing, China |
推荐引用方式 GB/T 7714 | Liu,Haitao,Li,Yuge,Liu,Dongchang. Object detection and recognition system based on computer vision analysis[J]. Journal of Physics: Conference Series,2021,1976(1). |
APA | Liu,Haitao,Li,Yuge,&Liu,Dongchang.(2021).Object detection and recognition system based on computer vision analysis.Journal of Physics: Conference Series,1976(1). |
MLA | Liu,Haitao,et al."Object detection and recognition system based on computer vision analysis".Journal of Physics: Conference Series 1976.1(2021). |
入库方式: OAI收割
来源:自动化研究所
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