Face age and gender recognition based on improved VGGNet algorithm
Year: 2019
Journal of Information and Computing Science, Vol. 14 (2019), Iss. 3 : pp. 217–226
Abstract
School of Mathematics and Statistics, Nanjing University of Information Science & Technology, Nanjing, 210044, China (Received February 20 2019, accepted June 24 2019) Recognition of age and gender based on face image is one of the hotspots of current artificial intelligence research. In this paper, an improved VGG+SENet algorithm is proposed to simplify the identification of age and gender algorithm by simplifying VGGNet model, improving the loss function and embedding the SENet module. Compared with other models, the improved network structure and loss function model proposed in this paper can quickly and accurately obtain output recognition results. Experimental results on multiple benchmark face datasets show that the proposed improved VGG+SENet algorithm has higher recognition accuracy than other related models based on deep learning.
Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2024-JICS-22416
Journal of Information and Computing Science, Vol. 14 (2019), Iss. 3 : pp. 217–226
Published online: 2019-01
AMS Subject Headings:
Copyright: COPYRIGHT: © Global Science Press
Pages: 10