Edge Face Recognition System Based on One-Shot Augmented Learning

  1. Diego M. Jiménez-Bravo 1
  2. Álvaro Lozano Murciego 1
  3. André Sales Mendes 1
  4. Luis Augusto Silva 1
  5. Daniel H. De La Iglesia 1
  1. 1 Universidad de Salamanca
    info

    Universidad de Salamanca

    Salamanca, España

    ROR https://ror.org/02f40zc51

Revista:
IJIMAI

ISSN: 1989-1660

Año de publicación: 2022

Título del ejemplar: Special Issue on New Trends in Disruptive Technologies, Tech Ethics and Artificial Intelligence

Volumen: 7

Número: 6

Páginas: 31-44

Tipo: Artículo

DOI: 10.9781/IJIMAI.2022.09.001 DIALNET GOOGLE SCHOLAR lock_openDialnet editor

Otras publicaciones en: IJIMAI

Resumen

There is growing concern among users of computer systems about how their data is handled. In this sense, IT (Information Technology) professionals are not unaware of this problem and are looking for solutions to meet the requirements and concerns of their users. During the last few years, various techniques and technologies have emerged that allow us to answer to the problem posed by users. Technologies such as edge computing and techniques such as one-shot learning and data augmentation enable progress in this regard. Thus, in this article, we propose the creation of a system that makes use of these techniques and technologies to solve the problem of face recognition and form a low-cost security system. The results obtained show that the combination of these techniques is effective in most of the face detection algorithms and allows an effective solution to the problem raised.

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Fuente de los datos: Dialnet