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Neural Networks in Video-Based Age and Gender Recognition on Mobile Platforms
Optical Memory and Neural Networks ( IF 1.0 ) Pub Date : 2019-02-01 , DOI: 10.3103/s1060992x18040021 A. S. Kharchevnikova , A. V. Savchenko
中文翻译:
视频时代的神经网络和移动平台上的性别识别
更新日期:2019-02-01
Optical Memory and Neural Networks ( IF 1.0 ) Pub Date : 2019-02-01 , DOI: 10.3103/s1060992x18040021 A. S. Kharchevnikova , A. V. Savchenko
Abstract
The paper considers the use of convolutional neural networks for the concurrent recognition of the gender and age of a person by video records of his face. The emphasis is on the incorporation of the approach into mobile video analytics systems. We have investigated the fusion of decisions obtained during the processing of each video frame, including the use of the classifier committee based on Dempster-Shafer theory. We propose the novel age prediction method using the evaluation of the expectation of the most probable ages. We have compared existing neural-net models with a specially trained modification of the MobileNet convolution network with two outputs. The experimental results are given for such data collections as Kinect, IJB-A, Indian Movie and EmotiW. As compared with other conventional methods, our approach makes it possible to increase the age and gender recognition accuracy by 2–5% and 5–10% respectively.中文翻译:
视频时代的神经网络和移动平台上的性别识别