Edge Face Recognition System Based on One-Shot Augmented Learning

Diego M. Jiménez-Bravo

doi:10.9781/ijimai.2022.09.001

Edge Face Recognition System Based on One-Shot Augmented Learning

2022-01-01

1

OA

AI

D

Diego M. Jiménez-Bravo *

Á

Álvaro Lozano Murciego

Daniel H. de la Iglesia

DOI：10.9781/ijimai.2022.09.001

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摘要

En 中文

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.

Keyword:

Data Augmentation

Edge Artificial Intelligence

Edge Computing

Face Recognition

One-Shot Learning

Security System

Edge Face Recognition System Based on One-Shot Augmented Learning

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