The system achieves non-resident face recognition attendance through intelligent face recognition technology, real-time detection and display of attendance results and abnormal/violation alarms, as well as statistical analysis and early warning of working hours, and support for stranger recognition alarms; body temperature detection and mask-wearing detection through target recognition technology and infrared temperature measurement technology, real-time display of results and abnormal alarms, and statistical analysis.

The system adopts deep learning algorithm centre engine mode, deep learning to achieve high precision and accuracy, the centre engine to access multiple videos to achieve cost reduction and maintenance. Relevant monitoring, testing video, centrally presented in the centre of the large screen, to achieve visual production.

Dihuge multi-person non-resident face recognition system is a system integrating hardware equipment and management system software based on advanced deep learning convolutional neural network algorithm and edge computing computer vision processing technology for the needs of high traffic attendance and security issues, public health epidemic prevention (body temperature monitoring + wearing a mask monitoring). Through intelligent face recognition technology, target detection technology, infrared temperature measurement technology, combined with the basic information of employees and work, the system realises intelligent face attendance, stranger recognition alarm, body temperature monitoring, mask wearing monitoring, and corresponding abnormal/violation alarms.