Title: The model of fast face recognition against age interference in deep learning

Authors: Yuzhe Zhang; Peilin Wu; Jinhui Zhao; Hao Feng; Rongtao Liao

Addresses: School of Automation (School of Artificial Intelligence), Hangzhou Dianzi University, Hangzhou 310018, China ' Information and Communication Branch of Hubei Epc, Wuhan 430077, China ' Information and Communication Branch of Hubei Epc, Wuhan 430077, China ' Information and Communication Branch of Hubei Epc, Wuhan 430077, China ' Information and Communication Branch of Hubei Epc, Wuhan 430077, China

Abstract: In order to overcome the low recognition efficiency of traditional anti-age face recognition methods, the paper proposes a new anti-age-disturbing face recognition modelling method based on deep learning. Firstly, build a standard face recognition information database and use this as the matching standard for face recognition. Then, construct a deep learning convolutional neural network, install the propagation process and training strategy of deep learning. Lastly, build an age discrimination model, a loss function and an objective function and solve it. On this basis, the facial features are extracted, after matching with the data in the standard database and similarity calculation, the final rapid facial recognition result is obtained. Experimental results show that the highest recognition accuracy of the designed face recognition model is 99.2%, and the recognition speed of the designed model is faster.

Keywords: deep learning; convolution neural network; anti age interference; face recognition model.

DOI: 10.1504/IJBM.2022.124668

International Journal of Biometrics, 2022 Vol.14 No.3/4, pp.223 - 238

Received: 29 May 2020
Accepted: 11 Aug 2020
Published online: 05 Aug 2022 *

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