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Age and Gender Prediction Using Convolutional Neural Networks

机译:使用卷积神经网络的年龄和性别预测

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摘要

Age has always been an important feature of our identity. It is also an important factor in our social life. Predictions of age made with artificial intelligence can be applied to many areas such as intelligent human-machine interface development, security, cosmetics, electronic commerce. In this study, face images of persons were trained using convolutional neural networks, and age and gender were tried to be predicted with high success rate. Inception V1 convolutional neural network model developed by Google was used for training. Inception V1 model is already trained in the VGGFace2 dataset. Transfer learning provided by Deep Learning, the dataset is trained on this model. The IMDB dataset with face images with gender and age tags was selected as the dataset. There are 460.723 images in this dataset. 260.428 pictures in the IMDB dataset are used for training. As a result of the study, achievement rate of 70.3% in age prediction and 97% in gender prediction has been achieved.
机译:年龄一直是我们身份的重要特征。这也是我们社会生活中的一个重要因素。用人工智能制造的年龄预测可以应用于许多领域,如智能人机界面开发,安全,化妆品,电子商务。在这项研究中,人们使用卷积神经网络培训人的面部图像,并试图以高成功率预测年龄和性别。谷歌开发的Inception V1卷积神经网络模型用于培训。 Inception V1模型已经在Vggface2数据集中培训。通过深度学习提供的传输学习,DataSet在此模型上培训。选择具有具有性别和年龄标记的IMDB数据集作为数据集。此数据集中有460.723个图像。 260.428 IMDB数据集中的图片用于培训。由于该研究的结果,已经实现了70.3%的成就率和性别预测中的97%。

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