Recognition system for increasing business potential from in-store customers.

В. Moroz; О. Syrotkina; А. Marochko

doi:10.36910/6775-2524-0560-2020-38-08

В. Moroz Dnipro University of Technology, https://orcid.org/0000-0002-5625-0864
О. Syrotkina Ukraine, Dnipro, University of Technology https://orcid.org/0000-0002-4069-6984
А. Marochko Ukraine, Dnipro, University of Technology

DOI: https://doi.org/10.36910/6775-2524-0560-2020-38-08

Keywords: Analytical system, effectiveness of the trade organization, algorithm analysis and research, modeling and forecasting results.

Abstract

This paper presents a comprehensive algorithm for creating a user recognition system to identify customers as well as collect, store, analyze and research data from a business. Its main features include synchronization with, and output to, an application installed on a PC or smartphone.

References

D ASSIS. [Electronic resource] // URL https://megacount.ru/3dassis.html

Deductor. [Electronic resource] // URL https://findface.pro

Asit Kumar Datta, Madhura Datta, Pradipta Kumar Banerjee: Face Detection and Recognition: Theory and Practice, 2016. –P. 152-159.

Manisha Omprakash: implementing face recognition in matlab, 2018. – P. 120-130.

Federica Marcolin: Neural Networks and Deep Learning, 2018. – P. 100-120.

Kelly Gates: Our Biometric Future: Facial Recognition Technology and the Culture of Surveillance, 2011. – P. 62-70.p.

Laura E. Miller, Ray Miller: That's Customer Focus!: The Overworked and Underappreciated Manager's Guide to Creating a Customer-Focused Organization, 2008. – P. 69-74.

Face++. [Electronic resource] // URL: https://www.faceplusplus.com/

DeepFace. [Electronic resource] // URL: https://deepface.ir/