Title
Classification and Prediction of Gender in Facial Images with CNN
Date Issued
01 January 2021
Access level
metadata only access
Resource Type
conference paper
Publisher(s)
Springer Science and Business Media Deutschland GmbH
Abstract
Computer technology development, the popularization of artificial intelligence, and facial recognition have become necessary for multiple applications. Both in the military and economic aspects, as it is gradually introduced into people’s lives, for example, in the use of facial recognition to unlock mobile phones. Since the 1990s, gender identification has begun to be studied through a photo of the face; it is worth mentioning that facial gender recognition is challenging in computer vision. This article is made to be applicable in marketing; in this way, it could offer differentiated products according to the clients’ gender. For this purpose, it has used public databases to classify the images of faces in men and women, with the implementation of a Convolutional Neural Network (CNN) model, which it obtained an efficiency in the classification of approximately 97%. It also carried out prediction tests in which the silver model achieved a hit rate of 86.25%.
Start page
53
End page
62
Volume
762 LNEE
Language
English
OCDE Knowledge area
Ingeniería de sistemas y comunicaciones
Subjects
Scopus EID
2-s2.0-85107315672
Source
Lecture Notes in Electrical Engineering
ISSN of the container
18761100
ISBN of the container
9783030722074
Sources of information:
Directorio de Producción Científica
Scopus