基于改进CNN的年龄和性别识别  

Age and gender classification using improved convolutional neural networks

作　　者：陈济楠 李少波[1,2] 高宗[1] 李政杰[1] 杨静[1] CHEN Jinan;LI Shaobo;GAO Zong;LI Zhengjie;YANG Jing(Key Laboratory of Advanced Manufacturing Technology of Ministry of Education,Guizhou University,Guiyang 550025,China;School of Mechanical Engineering,Guizhou University,Guiyang 550025,China)

机构地区：[1]贵州大学现代制造技术教育部重点实验室,贵阳550025 [2]贵州大学机械工程学院,贵阳550025

出　　处：《计算机工程与应用》2018年第16期135-139,175,共6页Computer Engineering and Applications

基　　金：国家自然科学基金(No.51475097);贵州大学面向智能装备领域的技术众筹研究生创新基地项目(No.JSZC[2016]004)

摘　　要：人脸图像的年龄和性别识别是人脸分析的重要任务,在真实多变场景下完成识别依然面临挑战。改进深度卷积神经网络(Convolutional Neural Network,CNN),将首层大尺寸卷积核替换为级联3×3卷积核;采用跨连卷积层融合中层和高层抽象特征;加入Batch Normalization(BN)层,设置较高的学习率和较小的Dropout比率;采用1×1卷积核与全局平均池化(Global Average Pooling)取代全连接层。实验表明,所提方法与主流的年龄性别识别方法比较具有较好的识别率,在Adience数据集上,年龄识别精度达到89.8%,性别识别精度达到93.3%。Automatic age and gender classification of face images is an important task for face analysis.However,there is currently no model of accurate age and gender classification for face images in real world.A deep Convolutional Neural Network（CNN）is proposed to complete the recognition task.The first layer of large-scale convolution filters is replaced by cascade 3×3 convolution filters.The last hidden layer is fully connected to both the average pooling and the fifth convolutional layers such that it sees multi-scale features（features in the fifth convolutional layer are more global than those in the average pooling layer）.Because of the use of Batch Normalization layer,a higher learning rate and a smaller Dropout ratio can be set.1×1 convolution filters and global average pooling over feature maps are utilized instead of the fully convolution.The results show that the convolutional neural network proposed in this paper is superior to other state-of-theart classification methods and achieves 89.8% accuracy on age classification,93.3% accuracy on gender classification on Adience dataset.

关 键 词：深度学习 卷积神经网络 年龄分类 性别识别 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]