Fabiana Vinci
Inclusive representation for Face Recognition analysis: an empirical investigation on critical issues and uncovered opportunities.
Rel. Antonio Vetro', Juan Carlos De Martin. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2023
Abstract
Face recognition technology is frequently used, in modern applications, in different fields: security, advertising, autonomous car, banks and education. A variety of recent works show the threats and limitations of this technology, regarding vulnerable subjects: black population, in particular black females, young population, LGBTQ+ community and many others. Face features (e.g. lips, cheeks, eyes) and their measurements are the most important features of face recognition algorithms. In this context, this study aims at finding if there are any limitations of the technology itself applied to a population characterized by slightly different facial features, Down syndrome people. Due to the high sensitivity of the subjects, few works have been proposed in the literature, and they are mostly concerned on the recognition of the Syndrome.
The current study includes the creation of a specific dataset, which was strictly related to the lack of existent resources of a dataset including Down syndrome population
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