
Prediction Of Gender From Facial Image Using Deep Learning Techniques
Gender Recognition
LAP Lambert Academic Publishing
Published on 17. August 2020
Book
Paperback/Softback
52 pages
978-620-2-79542-5 (ISBN)
Description
Gender recognition is a process of recognizing a person's gender from their facial image using deep learning. The posed variation, illumination, and occlusion are some of the factors that affect in recognizing faces. These are reduced by increasing the accuracy of prediction. The network used for training the system is Convolutional Neural Network (CNN). For improving accuracy, the faces are detected and cropped from the image. Face detection is done using Open CV which detects the face by the frontal features of the face. This is done during training the network. The dataset used for training has cropped images.
More details
Language
English
Dimensions
Height: 220 mm
Width: 150 mm
Thickness: 4 mm
Weight
96 gr
ISBN-13
978-620-2-79542-5 (9786202795425)
Schweitzer Classification
Persons
There are several challenges in gender recognition which makes face image analysis difficult such as pose, scaling, capturing factors like blurring, noise, and resolution. Even, age can make a difference in the classification accuracy. The adult face will give more efficient results than kids.