Result: Feasibility Enterprise Time and Attendance System Using Artificial Vision Based on Neural Networks with Python and Raspberry Pi

Title:
Feasibility Enterprise Time and Attendance System Using Artificial Vision Based on Neural Networks with Python and Raspberry Pi
Authors:
Alex Nú nez, Johnny Jácome, Kerly Vaca, Braulio Balseca, Ramiro Jara
Source:
ESPOCH Congresses, Vol 3, Iss 2, Pp 72-84 (2024)
Publisher Information:
Knowledge E
Publication Year:
2024
Collection:
Directory of Open Access Journals: DOAJ Articles
Subject Terms:
facial recognition, python, raspberry pi, artificial neural networks, machine learning, Science (General), Q1-390
Document Type:
Academic journal article in journal/newspaper
Language:
Spanish; Castilian
Relation:
https://doi.org/10.18502/espoch.v4i1.15803; https://doaj.org/toc/2789-5009; https://doaj.org/article/44ada9ed53ee4501880936ba344b3e3f
DOI:
10.18502/espoch.v4i1.15803
Availability:
https://doi.org/10.18502/espoch.v4i1.15803
https://doaj.org/article/44ada9ed53ee4501880936ba344b3e3f
Accession Number:
edsbas.82FBDDDA
Database:
BASE

Further Information

The objective of this article is to model a facial recognition system, using a Raspberry PI and Machine Learning (ML), for an attendance control system. Machine learning is a branch of artificial intelligence that allows the training of algorithms inspired by biological systems, using a considerable amount of information. In this work, the architecture of artificial neural networks with error backpropagation has been used, which have a certain similarity with human neurons and can extract knowledge from the input data. The algorithms have been implemented in Python and the results show a high precision for the classification and recognition of people.