Face Gender Recognition in the Wild: An Extensive Performance Comparison of Deep-Learned, Hand-Crafted, and Fused Features with Deep and Traditional Models

Face Gender Recognition in the Wild: An Extensive Performance Comparison of Deep-Learned, Hand-Crafted, and Fused Features with Deep and Traditional Models

Face gender recognition has many useful applications in human–robot interactions as it can improve the overall user experience. Support vector machines (SVM) and convolutional neural networks (CNNs) have been used successfully in this domain. Researchers have shown an increased interest in comparing...

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Bibliographic Details
Main Authors: Alhanoof Althnian, Nourah Aloboud, Norah Alkharashi, Faten Alduwaish, Mead Alrshoud, Heba Kurdi
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Applied Sciences
Subjects:
deep learning
gender recognition
CNN
SVM
deep-learned features
hand-crafted features
Online Access:https://www.mdpi.com/2076-3417/11/1/89

Internet

https://www.mdpi.com/2076-3417/11/1/89

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