Detección de tapabocas en imágenes para la prevención del COVID-19 a través de redes neuronales
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Fecha
2021
Autores
Ruiz Caicedo, Franklin De Jesús
Anillo Polo, Luis Enriques
Meléndez Gutiérrez, María José
Mejía Toro, Moisés Alfonso
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Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
A finales del año 2019 apareció un nuevo virus denominado COVID-19, el cual ha afectado a muchos países alrededor del mundo y ha generado muchas muertes. Este virus entra al cuerpo por tres medios: ojos, nariz y boca. La organización mundial de la salud ordenó el uso indispensable de mascarillas en espacios públicos, personal de la salud y en personas infectadas, y el lavado constante de las manos para así prevenir la expansión de este virus y evitar mayores consecuencias a la población en general.
Debido a la falta de concientización acerca del virus, y por ende el uso inadecuado o simplemente el no usar mascarillas en espacios públicos, se ha generado un mayor número de contagios en este país, ocasionando un aumento en el sistema de salud. A pesar de todas estas normas, una pequeña parte de la población aún no se concientiza y estos siguen propagando el virus. En este trabajo proponemos un algoritmo que procese las diferentes imágenes que recibe y analiza a través de redes neuronales si la persona tiene o no mascarilla para así hacer su respectiva detección y llamado de atención y por ende prevenir la expansión del covid-19.
At the end of 2019, a new virus called COVID-19 appeared, which has affected many countries around the world and has caused many deaths. This virus enters the body by three means: eyes, nose, and mouth. The world health organization ordered the essential use of masks in public spaces, health personnel and infected people, and the constant washing of hands in order to prevent the spread of this virus and avoid greater consequences for the general population. Due to the lack of awareness about the virus, and therefore the inappropriate use or simply not wearing masks in public spaces, a greater number of infections has been generated in this country, causing an increase in the health system. Despite all these norms, a small part of the population is still not aware and they continue to spread the virus. In this work we propose an algorithm that processes the different images that it receives and analyzes through neural networks whether or not the person has a mask in order to make their respective detection and call for attention and therefore prevent the spread of covid-19.
At the end of 2019, a new virus called COVID-19 appeared, which has affected many countries around the world and has caused many deaths. This virus enters the body by three means: eyes, nose, and mouth. The world health organization ordered the essential use of masks in public spaces, health personnel and infected people, and the constant washing of hands in order to prevent the spread of this virus and avoid greater consequences for the general population. Due to the lack of awareness about the virus, and therefore the inappropriate use or simply not wearing masks in public spaces, a greater number of infections has been generated in this country, causing an increase in the health system. Despite all these norms, a small part of the population is still not aware and they continue to spread the virus. In this work we propose an algorithm that processes the different images that it receives and analyzes through neural networks whether or not the person has a mask in order to make their respective detection and call for attention and therefore prevent the spread of covid-19.
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Palabras clave
Visión computacional, Redes neuronales, Rede neuronal convolucional, Computational vision, Neural networks, Convolutional neural network