Detection and Classification of Gender-Type Using Convolution Neural Network

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Abstract
Deep learning has a vital role in computer vision to discover things. Deep learning techniques, especially convolutional neural networks, are being exploited in identifying and extracting relevant features of a specific set of images. In this research we suggested that it could help in detecting the gender-type of individuals and classifying them using convolutional neural networks, as it achieved superior predictive performance in classifying individuals according to gender, and the experimental results showed that the proposed system works accurately and efficiently, which gives an accuracy rate of 97.76%.
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Archival date: 2021-01-07
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