2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDMMSP-1.3
Paper Title A Multi-layer Multi-channel Attentive Network for Gender and Age Recognition
Authors Jia Chen, Haiping Yu, Yimei Kang, Beihang University, China
SessionMMSP-1: Multimedia Signal Processing
LocationGather.Town
Session Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Time:Tuesday, 08 June, 14:00 - 14:45
Presentation Poster
Topic Multimedia Signal Processing: Emerging Areas in Multimedia
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract In practical application, the existing gender and age recognition algorithms can't meet the requirements of both small-sized model and high accuracy simultaneously. Moreover, most models based on CNNs have a even larger size of more than 200M. In this paper a multi-layer multi-channel attentive network based on the idea of divide-and-conquer is proposed. This method uses multi-layer processes in each channel to extract features of different layers and improves accuracy by layer refinement. We use some dynamic parameters to fine-tune each layer to make the model fit better. Each layer uses the same classifier to reduce parameters to make the model smaller. And we import attention mechanisms to increase the ability of the network to use the features. Experiments show that the accuracy of this method is better than several mainstream networks and the size of the model is less than 0.5M, which can be used in mobile terminals well.