关键词: 低分辨率, 年龄识别, 深度学习, 时间复杂度

Abstract:  If the accessed facial image is of low resolution, facial wrinkles and other characteristics of the information would often be lost, undermining the performance of age identification. In view of the existing age identification method lacking this research field and in order to solve this problem, this paper proposed an age identification method for low-resolution images by reconstructing the input low-resolution face images using conditional generative adversarial net (CGAN), and then identifying the age using the deep learning method. Firstly, a comparative experiment on image reconstruction was carried out, and then the results of age recognition were compared on different face image data sets. The experimental comparison with other deep learning methods on signal noise ratio, peak signal noise ratio, and mean absolute error shows the effectiveness of the proposed method in image reconstruction and age recognition. In addition, the time complexity of the proposed method was also analyzed. 

Key words: low resolution, age recognition, deep learning, time complexity