Using Feature Fusion and Parameter Optimization of Dual-input Convolutional Neural Network for Face Gender Recognition

Using Feature Fusion and Parameter Optimization of Dual-input Convolutional Neural Network for Face Gender Recognition

In recent years, convolutional neural networks (CNNs) have been successfully used in image recognition and image classification. General CNNs only use a single image as feature extraction. If the quality of the obtained image is not good, it is easy to cause misjudgment or recognition error. Therefo...

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Bibliographic Details
Main Authors: Cheng-Jian Lin, Cheng-Hsien Lin, Shiou-Yun Jeng
Format: Article
Language:English
Published: MDPI AG 2020-05-01
Series:Applied Sciences
Subjects:
convolutional neural network
gender classification
feature fusion
uniform experimental design
AlexNet
Online Access:https://www.mdpi.com/2076-3417/10/9/3166

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