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Research And Implementation Of Facialnet Based On Convolutional Neural Network

机译:基于卷积神经网络的FACIALNET的研究与实现

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Deep learning, artificial intelligence and other cutting-edge technologies are constantly being integrated into people's daily lives. Even small vending machines that can be seen everywhere in life have begun to use facial payment methods. The detection and recognition of face images is no longer unattainable, but the analysis and recognition of face information and characteristics (gender, age, race, etc.) is still not fully mature, in order to improve the accuracy of face information recognition In this paper, a face information recognition model is designed. The feature extraction part uses an eight-layer convolutional neural network, and then uses two fully connected modules as the classifiers for gender recognition and age recognition. The experimental results show that the model uses the advantages of the convolutional neural network so that the model can predict the gender and age of the face more accurately.
机译:深入学习,人工智能和其他尖端技术不断融入人们的日常生活中。甚至在生活中可以看到的小型自动售货机已经开始使用面部付款方式。面部图像的检测和识别不再是无法实现的,但对面部信息和特征(性别,年龄,种族等)的分析和识别仍然没有完全成熟,以提高面部信息识别的准确性纸张,设计了一种面部信息识别模型。特征提取部分使用八层卷积神经网络,然后使用两个完全连接的模块作为性别识别和年龄识别的分类器。实验结果表明,该模型利用卷积神经网络的优势,使模型可以更准确地预测面部的性别和年龄。

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