Development of an artificial vision algorithm with neural networks for the detection of faces for the industrial sector (#474)

Authors

León León, Ryan Abraham

Chinchay Otiniano, Yeremi Eymail

Vargas Orihuela, Fiorela Geraldine

Abstract

In this study, a facial recognition system was developed using computer neural networks and the Python programming language. The system was implemented on an HP laptop, equipped with an Intel Core i7 processor and running the 64-bit Windows 10 operating system. The main objective was to improve efficiency and security in the identification and authentication of individuals across different areas. Facial images were captured using a webcam connected to the laptop, and facial recognition algorithms based on machine learning techniques were applied. The results revealed a 95% accuracy in accurately identifying individuals from the analyzed facial images. These findings highlight the effectiveness of the implemented system and its potential to enhance security in industrial facilities, access control, and personnel management. Moreover, the implementation of the system in Chimbote, Peru, has the potential to drive technological development and innovation in the region, creating employment opportunities and contributing to local economic growth.