Face recognition algorithm based on improved neural network

Chenyu Huang

doi:10.1117/12.2671658

16 March 2023 Face recognition algorithm based on improved neural network

Chenyu Huang

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125930J (2023) https://doi.org/10.1117/12.2671658
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

In complex environment, the performance of traditional face recognition algorithm decreases greatly. In order to further improve the recognition accuracy of current face recognition algorithms, this paper proposes two face recognition algorithms based on improved convolutional neural networks through the analysis of the defects of traditional algorithms. Finally, we will build a new face recognition model to verify the effectiveness of the two new methods. The first method is to extract and classify face features by fusing convolution layer and pooling layer, train neural network by stochastic gradient descent method, recognize face by Softmax classifier, and finally solve the over-fitting problem by "Dropout" method. The second method is to use the network link structure of bisymmetric LetNet and DCT-LBP joint processing method to process the input image. The two algorithms have some similarities, and both can improve the accuracy of face recognition.

Citation Download Citation

Chenyu Huang "Face recognition algorithm based on improved neural network", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125930J (16 March 2023); https://doi.org/10.1117/12.2671658

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