Open AccessQT display interface design of new retail system based on computer vision
Author(s) -
Yali Wang,
Jinghao Ma,
Xinke Zhang,
Jun Jiang,
Shen Ming
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1792/1/012085
Subject(s) - settlement (finance) , interface (matter) , process (computing) , computer science , code (set theory) , commodity , workload , identification (biology) , human–computer interaction , multimedia , business , world wide web , finance , operating system , botany , set (abstract data type) , bubble , maximum bubble pressure method , payment , biology , programming language
With the rapid development of science and technology, the application of computer vision is more and more widely, and there are great changes in all walks of life. New retail can rely on this advantage to improve the intelligent settlement of supermarket and reduce the workload of supermarket staff. In this paper, we use deep learning to train the goods that need to be settled, and identify the goods in the video during the settlement. At the settlement interface, Alipay two-dimensional code is generated to sweep the code for customers. QT is used to display the process of commodity identification and settlement.