Modelos de aprendizaje automático en la detección e identificación de personas
una revisión de literatura
Introducción: Este artículo es el resultado de la investigación titulada " Desarrollo de un prototipo para optimizar las condiciones de acceso al SENA-Pescadero utilizando inteligencia artificial y herramientas de código abierto", desarrollada en el Servicio Nacional de Aprendizaje en 2020.
Problema: ¿Cómo identificar las técnicas de aprendizaje automático aplicadas a los procesos de visión por computador a través de una revisión bibliográfica?
Objetivo: Determinar la aplicación, así como las ventajas y desventajas de las técnicas de aprendizaje automático enfocadas a la detección e identificación de personas.
Metodología: Revisión sistemática de la literatura en 4 bases de datos bibliográficas y científicas de alto impacto, utilizando filtros de búsqueda y criterios de selección de información.
Resultados: Técnicas de aprendizaje automático definidas como Análisis de Componentes Principales, Codificación Local de Coordenadas Regularizada de Etiquetas Débiles, Máquinas de Vectores de Soporte, Clasificadores en Cascada de Haar y EigenFaces y FisherFaces, así como su aplicabilidad en procesos de detección e identificación.
Conclusiones: La investigación permitió identificar las principales técnicas de inteligencia computacional basadas en machine learning aplicadas a la detección e identificación de personas. Su influencia se mostró en varios casos de aplicación, pero la mayoría de ellos se centraron en la implementación y optimización de sistemas de control de acceso, o tareas en las que se requería la identificación de personas para la ejecución de procesos
Originalidad: A través de esta investigación se estudiaron y definieron las principales técnicas de machine learning utilizadas actualmente para la detección e identificación de personas.
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Derechos de autor 2022 Ingeniería Solidaria
Esta obra está bajo una licencia internacional Creative Commons Atribución 4.0.
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El autor se compromete a esperar el resultado de evaluación de la revista Ingeniería Solidaria, antes de considerar su presentación a otro medio; en caso de que la respuesta de publicación sea positiva, adicionalmente, se compromete a responder por cualquier acción de reivindicación, plagio u otra clase de reclamación que al respecto pudiera sobrevenir por parte de terceros.
Asimismo, debe declarar que, como autor o coautor, está de acuerdo por completo con los contenidos presentados en el trabajo y ceder todos los derechos patrimoniales, es decir, su reproducción, comunicación pública, distribución, divulgación, transformación, puesta a disposición y demás formas de utilización de la obra por cualquier medio o procedimiento, por el término de su protección legal y en todos los países del mundo, al Fondo Editorial de la Universidad Cooperativa de Colombia, de manera gratuita y sin contraprestación presente o futura.
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