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14 November 2023 Research on MobileNet-based lightweight face recognition algorithm
Jian Yang, Xiaozhi Yang, Chuan Wang, Huanfeng Zhang, Yanglan Zhang
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Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129340O (2023) https://doi.org/10.1117/12.3008092
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China
Abstract
A lightweight face recognition algorithm based on MobileNet is proposed in this paper to address limited computational power and storage resources in patient recognition by mobile nursing robots. Firstly, MobileNet-v2 is used as the backbone network, and redundant Block blocks are pruned to reduce the number of parameters. Secondly, ShuffleNet's spatially separable convolution is introduced in the residual blocks to increase network parallelism. Finally, the original Softmax loss function is replaced with an improved ArcFace loss function, which includes a Taylor expansion in the Target logit value, to enhance network constraint and achieve better separability. Experimental results show that the improved face recognition algorithm achieves a combined recognition rate of 97% and a combined average speed of 0.725 s, fulfilling the goal of designing a lightweight and efficient deep learning network.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Jian Yang, Xiaozhi Yang, Chuan Wang, Huanfeng Zhang, and Yanglan Zhang "Research on MobileNet-based lightweight face recognition algorithm", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129340O (14 November 2023); https://doi.org/10.1117/12.3008092
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KEYWORDS
Facial recognition systems
Convolution
Detection and tracking algorithms
Network architectures
Deep learning
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