Machine vision model for the opening of an office access door

Authors

  • Ivan Carlo Petrlik Azabache Universidad Nacional Mayor de San Marcos. Lima, Peru https://orcid.org/0000-0002-1201-2143
  • Ciro Rodriguez Rodriguez Universidad Nacional Mayor de San Marcos. Lima, Peru

DOI:

https://doi.org/10.15381/risi.v15i2.23972

Keywords:

Computer vision, Neural networks, SOAR, Bioinspiration

Abstract

The objective of this work is to present a proposed SOAR Artificial Cognitive Architecture Model based on the process of vision, pattern recognition and decision making performed by human beings. The environment must guarantee certain preconditions for its correct operation. Our prototype artificial cognitive architecture system is bio-inspired in the way humans work to determine if a person is known or not.

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Published

2022-12-30

Issue

Vol. 15 No. 2 (2022)

Section

Original Research Articles

License

Copyright (c) 2022 Ivan Carlo Petrlik Azabache, Ciro Rodriguez Rodriguez

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

AUTHORS RETAIN THEIR RIGHTS:

a. Authors retain their trade mark rights and patent, and also on any process or procedure described in the article.

b. Authors retain their right to share, copy, distribute, perform and publicly communicate their article (eg, to place their article in an institutional repository or publish it in a book), with an acknowledgment of its initial publication in the Revista de investigación de Sistemas e Informática. 

c. Authors retain theirs right to make a subsequent publication of their work, to use the article or any part thereof (eg a compilation of his papers, lecture notes, thesis, or a book), always indicating its initial publication in the Revista de investigación de Sistemas e Informática (the originator of the work, journal, volume, number and date).

How to Cite

[1]
“Machine vision model for the opening of an office access door”, Rev.Investig.sist.inform., vol. 15, no. 2, pp. 19–26, Dec. 2022, doi: 10.15381/risi.v15i2.23972.