Object detection and recognition system based on computer vision analysis

doi:10.1088/1742-6596/1976/1/012024

CORC > 自动化研究所 > 中国科学院自动化研究所 > 综合信息系统研究中心 > 脑机融合与认知评估

	Object detection and recognition system based on computer vision analysis
	Liu,Haitao 1; Li,Yuge 2; Liu,Dongchang 1
刊名	Journal of Physics: Conference Series
	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
出版者	IOP Publishing
WOS记录号	IOP:1742-6588-1976-1-012024
内容类型	期刊论文
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).