Artificial vision system to recommend professional profiles through facial and text recognition
DOI:
https://doi.org/10.56162/transdigital362Keywords:
computer vision, facial recognition, handwriting recognition, professional profiling, vocational orientationAbstract
This research developed a computer vision system that uses facial and text recognition to recommend professional profiles. This with the aim of improving vocational guidance and personnel recruitment. The process was carried out at the Technological Higher Studies of Ecatepec, Mexico. The system employs advanced image processing and machine learning techniques in Python to evaluate facial and handwriting features. The results showed an accuracy of 87.5% in facial analysis and 85.93% in text analysis. Furthermore, an overall accuracy of 86.72% was achieved by combining facial and text analysis. Users indicated that they were satisfied with the recommendations received. However, ethical concerns are highlighted about possible discrimination when using artificial intelligence. Despite these challenges, the system represents a novel and effective tool for assigning professional profiles, benefiting both students and companies in the orientation and selection process.
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Copyright (c) 2024 Emmanuel Tonatihu Juárez Velázquez, Derlis Hernández Lara, Carlos Alfonso Trejo Villanueva
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