Object detection and recognition system based on computer vision analysis
Liu,Haitao1; Li,Yuge2; Liu,Dongchang1
发表期刊Journal of Physics: Conference Series
ISSN1742-6588
2021-07-01
卷号1976期号:1
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.
关键词post-epidemic artificial intelligence computer vision deep learning
DOI10.1088/1742-6596/1976/1/012024
语种英语
WOS记录号IOP:1742-6588-1976-1-012024
出版者IOP Publishing
七大方向——子方向分类目标检测、跟踪与识别
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/45791
专题多模态人工智能系统全国重点实验室_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
第一作者单位中国科学院自动化研究所
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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).
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