Detección de nivel de Fotodaño por medio de inteligencia artificial en rostros usando luz ultra violeta para tratamiento con medicina regenerativa

Roberto Contrera Masse; Ana Silvia Moheno Contreras; Alberto Ochoa Zezzatti; Esteban Manuel Guevara Galván; César Alejandro Romero Hernández

doi:10.61273/neyart.v2i4.81

Authors

Roberto Contrera Masse National Technological Institute of Mexico https://orcid.org/0000-0001-9030-2456
Ana Silvia Moheno Contreras Autonomous University of Ciudad Juarez https://orcid.org/0009-0009-1107-1326
Alberto Ochoa Zezzatti Autonomous University of Ciudad Juarez https://orcid.org/0000-0002-9183-6086
Esteban Manuel Guevara Galván National Technological Institute of Mexico https://orcid.org/0009-0002-3050-6697
César Alejandro Romero Hernández National Technological Institute of Mexico https://orcid.org/0009-0001-4505-9079

DOI:

https://doi.org/10.61273/neyart.v2i4.81

Keywords:

Artificial Intelligence, Clustering, Decision Making, Machine Learning, K-means

Abstract

This research seeks to develop a work tool that helps in the detection of photosolar damage by applying artificial intelligence. The methodology encompasses everything from the acquisition of the digital image, the necessary elements to create the appropriate environment with UV light, and the creation of a graphical interface that facilitates the use of this research for people who are not familiar with artificial intelligence or programming languages. During the execution of tests, new problems are found that are favorably resolved by applying other non-supervised machine learning techniques.

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